{"data":[{"id":"10.5281/zenodo.20600005","type":"dois","attributes":{"doi":"10.5281/zenodo.20600005","identifiers":[{"identifier":"oai:zenodo.org:20600005","identifierType":"oai"}],"creators":[{"name":"Zambrana, José Victor","nameType":"Personal","givenName":"José Victor","familyName":"Zambrana","affiliation":[{"name":"University of Michigan–Ann Arbor","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0003-0107-6173","nameIdentifierScheme":"ORCID"}]},{"name":"Chen, Boshu","nameType":"Personal","givenName":"Boshu","familyName":"Chen","affiliation":[{"name":"University of Michigan–Ann Arbor","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]}],"titles":[{"title":"Hemagglutination inhibition and alternate serologic responses following Influenza A(H3N2) virus infection - R notebook"}],"publisher":{"name":"Zenodo"},"container":{},"publicationYear":2026,"subjects":[],"contributors":[],"dates":[{"date":"2026-06-08","dateType":"Issued"}],"language":null,"types":{"ris":"COMP","bibtex":"misc","citeproc":"article","schemaOrg":"SoftwareSourceCode","resourceType":"","resourceTypeGeneral":"ComputationalNotebook"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20600004","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"This project analyses antibody response patterns following PCR-confirmed H3N2influenza infection in a household cohort. Participants are classified intoresponse groups based on haemagglutination inhibition (HAI) and alternateantibody assays (full-length HA, HA stalk, neuraminidase). The analysisexamines how pre-exposure antibody titers predict response group membershipusing multinomial and logistic regression, with sensitivity analyses acrossH3N2 strains and age strata.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20600005","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-06-15T20:51:11Z","registered":"2026-06-15T20:51:11Z","published":null,"updated":"2026-06-15T20:51:11Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20600004","type":"dois","attributes":{"doi":"10.5281/zenodo.20600004","identifiers":[],"creators":[{"name":"Zambrana, José Victor","nameType":"Personal","givenName":"José Victor","familyName":"Zambrana","affiliation":[{"name":"University of Michigan–Ann Arbor","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0003-0107-6173","nameIdentifierScheme":"ORCID"}]},{"name":"Chen, Boshu","nameType":"Personal","givenName":"Boshu","familyName":"Chen","affiliation":[{"name":"University of Michigan–Ann Arbor","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]}],"titles":[{"title":"Hemagglutination inhibition and alternate serologic responses following Influenza A(H3N2) virus infection - R notebook"}],"publisher":{"name":"Zenodo"},"container":{},"publicationYear":2026,"subjects":[],"contributors":[],"dates":[{"date":"2026-06-08","dateType":"Issued"}],"language":null,"types":{"ris":"COMP","bibtex":"misc","citeproc":"article","schemaOrg":"SoftwareSourceCode","resourceType":"","resourceTypeGeneral":"ComputationalNotebook"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20600004","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"This project analyses antibody response patterns following PCR-confirmed H3N2influenza infection in a household cohort. Participants are classified intoresponse groups based on haemagglutination inhibition (HAI) and alternateantibody assays (full-length HA, HA stalk, neuraminidase). The analysisexamines how pre-exposure antibody titers predict response group membershipusing multinomial and logistic regression, with sensitivity analyses acrossH3N2 strains and age strata.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20600004","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":1,"versionOfCount":1,"created":"2026-06-15T20:51:11Z","registered":"2026-06-15T20:51:11Z","published":null,"updated":"2026-06-15T20:51:11Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5061/dryad.2z34tmpz8","type":"dois","attributes":{"doi":"10.5061/dryad.2z34tmpz8","identifiers":[],"creators":[{"name":"Bishop, Sasha G.D.","nameType":"Personal","givenName":"Sasha G.D.","familyName":"Bishop","affiliation":[{"name":"University of Michigan","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0877-3951","nameIdentifierScheme":"ORCID"}]},{"name":"Stinchcombe, John","nameType":"Personal","givenName":"John","familyName":"Stinchcombe","affiliation":[{"name":"University of Toronto","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/03dbr7087","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3349-2964","nameIdentifierScheme":"ORCID"}]},{"name":"Baucom, Regina","nameType":"Personal","givenName":"Regina","familyName":"Baucom","affiliation":[{"name":"University of Michigan","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7960-498X","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Data and code from: A resurrection experiment reveals reduced adaptive potential in a common agricultural weed"}],"publisher":{"name":"Dryad","schemeUri":"https://ror.org/","publisherIdentifier":"https://ror.org/00x6h5n95","publisherIdentifierScheme":"ROR"},"container":{},"publicationYear":2026,"subjects":[{"subject":"FOS: Natural sciences","schemeUri":"https://web-archive.oecd.org/2012-06-15/138575-38235147.pdf","subjectScheme":"fos"},{"subject":"FOS: Natural sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"floral traits"},{"subject":"resurrection experiment"},{"subject":"Quantitative genetics"},{"subject":"Global Change"},{"subject":"adaptation"},{"subject":"Pollination","schemeUri":"https://github.com/PLOS/plos-thesaurus","subjectScheme":"PLOS Subject Area Thesaurus"}],"contributors":[],"dates":[{"date":"2025-06-23T22:21:39Z","dateType":"Created"},{"date":"2026-06-01T22:05:11Z","dateType":"Submitted"},{"date":"2026-06-15T00:00:00Z","dateType":"Issued"},{"date":"2026-06-15T00:00:00Z","dateType":"Available"}],"language":"en","types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","relatedIdentifier":"10.1101/2025.06.03.657543","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["438991 bytes"],"formats":[],"version":"6","rightsList":[{"rights":"Creative Commons Zero v1.0 Universal","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc0-1.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Adaptive evolution is critical to population response to anthropogenic\n global change. Despite research suggesting adaptation commensurate with\n the rate of contemporary environmental change is possible, mismatches\n between expected and realized evolution in natural systems are widespread.\n Using a combination of quantitative genetics and resurrection ecology, we\n show that covariances among pollination and mating system related traits\n in the common morning glory (Ipomoea purpurea) constrain the rate of\n evolution and that such constraints are strengthening over time,\n dramatically reducing adaptive potential. Pollinator-attracting traits\n evolved or became more favored on a rapid time scale of less than ten\n years, but genetic covariances between traits limited the adaptive rate\n and evolutionary trajectory of flowering phenology, a trait with widely\n recognized importance in adapting to climatic shifts. ","descriptionType":"Abstract"},{"description":"#A resurrection experiment reveals reduced adaptive potential in a common\n agricultural weed DOI:\n https://datadryad.org/dataset/doi:10.5061/dryad.2z34tmpz8 --- ##\n Description of the data and file structure All datasheets come from a\n single, shared resurrection experiment conducted in a field environment.\n Due to vole herbivory and plant death in the field, not all plants had all\n traits measured, so traits measured together have their own data files\n (DataS1_floralMorph, DataS2_brix, DataS3_doffLC) for the sake of including\n all measurements. There is also a collated data file (DataS4_collated)\n including only plants with all traits measured for the sake of\n standardization across traits and multivariate analyses. Plant ID,\n Population, Block, and Maternal line are shared across all data sheets\n (i.e., Population 1 in the DataS1 spreadsheet is the same population as\n Population 1 in DataS2-5). ### Five .csv data files #### 1.\n DataS1_floralMorph.csv This dataset includes floral morphology\n measurements from 3-5 flowers/plant in a resurrection experiment done with\n *Ipomoea purpurea* (the common morning glory). Seeds were collected from 7\n populations in the SE United States at two time points, 2003 [ancestral]\n and 2012 [descendant], and grown together in a common garden field\n experiment. Floral measurements included are corolla width, corolla\n length, and the distance between the tallest anther and stigma\n (anther-stigma distance). ##### Columns: * ID - ID number assigned to each\n individual plant measured in the resurrection experiment * CorollaWidth -\n corolla width; measurement (in mm) of the diameter of the corolla *\n CorollaLength - corolla length; measurement (in mm) from the base of the\n sepal to the outer edge of the corolla * ASD - anther-stigma distance;\n difference between the length of the tallest anther (measurement in mm\n from the base of the sepal to the tip of the tallest anther) and the\n stigma (measurement in mm from the base of the sepal to the tip of the\n stigma) * LeafCount - total number of leaves on a plant at the time of\n first flowering * count - total number of seeds produced by a plant * Pop\n - ID number assigned to each unique, naturally occurring, population from\n which seeds were collected * Year - year (either 2003 or 2012) in which\n seeds were collected from naturally occurring populations * ML - ID\n assigned to each maternal line represented from field collections * Block\n - three sub-areas within the common garden representing possible spatial\n variation in environment across the common garden site. Population and\n maternal line sampling is identical within each block * Lat - latitude for\n each population * Long - longitude for each population * relFit - relative\n fitness; total seed count divided by mean seed count #### 2.\n DataS2_brix.csv This dataset includes measurements of nectar sucrose\n content [in degrees Brix] from 3-5 flowers/plant in a resurrection\n experiment done with Ipomoea purpurea (the common morning glory). Seeds\n were collected from 7 populations in the SE United States at two time\n points, 2003 [ancestral] and 2012 [descendant], and grown together in a\n common garden field experiment. ##### Columns: * ID - ID number assigned\n to each individual plant measured in the resurrection experiment * brix -\n measurement of the sucrose content of the nectar in a flower using the\n Brix scale and recorded from a pocket refractometer * LeafCount - total\n number of leaves on a plant at the time of first flowering * count - total\n number of seeds produced by a plant * Pop - ID number assigned to each\n unique, naturally occurring, population from which seeds were collected *\n Year - year (either 2003 or 2012) in which seeds were collected from\n naturally occurring populations * ML - ID assigned to each maternal line\n represented from field collections * Block - three sub-areas within the\n common garden representing possible spatial variation in environment\n across the common garden site. Population and maternal line sampling is\n identical within each block * Lat - latitude for each population * Long -\n longitude for each population * relFit - relative fitness; total seed\n count divided by mean seed count #### 3. DataS3_doffLC.csv This dataset\n includes the date of first flower (in Julian Date) and leaf count at\n flowering for each surviving plant [839 in total] in a resurrection\n experiment done with Ipomoea purpurea (the common morning glory). Seeds\n were collected from 7 populations in the SE United States at two time\n points, 2003 [ancestral] and 2012 [descendant], and grown together in a\n common garden field experiment. ##### Columns: * ID - ID number assigned\n to each individual plant measured in the resurrection experiment *\n JulianDate - date on which the first flower of a plant opens, synonymous\n with days after planting; converted into Julian Date * LeafCount - total\n number of leaves on a plant at the time of first flowering * count - total\n number of seeds produced by a plant * Pop - ID number assigned to each\n unique, naturally occurring population from which seeds were collected *\n Year - year (either 2003 or 2012) in which seeds were collected from\n naturally occurring populations * ML - ID assigned to each maternal line\n represented from field collections * Block - three sub-areas within the\n common garden representing possible spatial variation in environment\n across the common garden site. Population and maternal line sampling is\n identical within each block * Lat - latitude for each population * Long -\n longitude for each population * relFit - relative fitness; total seed\n count divided by mean seed count #### 4. DataS4_collated.csv This dataset\n includes all trait measurements (corolla width, corolla length,\n anther-stigma distance, nectar sucrose content, date of first flower, leaf\n count, and total seed count) combined together in a single dataset and\n restricted to plants for which there are measurements for every trait.\n This data comes from a resurrection experiment done with Ipomoea purpurea\n (the common morning glory). Seeds were collected from 7 populations in the\n SE United States at two time points, 2003 [ancestral] and 2012\n [descendant], and grown together in a common garden field experiment.\n ##### Columns: * ID - ID number assigned to each individual plant measured\n in the resurrection experiment * Pop - ID number assigned to each unique,\n naturally occurring population from which seeds were collected * Year -\n year (either 2003 or 2012) in which seeds were collected from naturally\n occurring populations * ML - ID assigned to each maternal line represented\n from field collections * Block - three sub-areas within the common garden\n representing possible spatial variation in environment across the common\n garden site. Population and maternal line sampling is identical within\n each block * Lat - latitude for each population * Long - longitude for\n each population * LeafCount - total number of leaves on a plant at the\n time of first flowering * count - total number of seeds produced by a\n plant * CW - corolla width; measurement (in mm) of the diameter of the\n corolla * CL - corolla length; measurement (in mm) from the base of the\n sepal to the outer edge of the corolla * ASD - anther-stigma distance;\n difference between the length of the tallest anther (measurement in mm\n from the base of the sepal to the tip of the tallest anther) and the\n stigma (measurement in mm from the base of the sepal to the tip of the\n stigma) * brix - measurement of the sucrose content of the nectar in a\n flower using the Brix scale and recorded from a pocket refractometer *\n JulianDate - date on which the first flower of a plant opens, synonymous\n with days after planting; converted into Julian Date #### 5.\n DataS5_polTrait.csv This dataset includes pollinator visitation data for a\n subset of 277 plants. Pollinator behavior surveys were conducted in\n 20-minute rounds with any pollinator approach or visitation to a flower\n recorder. For each plant observed, the average corolla width, length,\n anther-stigma distance, and brix were also recorded for the day of\n observation along with the day of first flower and leaf count for the\n plant. ##### Columns: * Year - year (either 2003 or 2012) in which seeds\n were collected from naturally occurring populations * Block - three\n sub-areas within the common garden representing possible spatial variation\n in environment across the common garden site. Population and maternal line\n sampling is identical within each block * Forage - residuals from a linear\n model of Forage ~ Block, taken to remove block effect from the SEM; Forage\n represents number of times within an observing period a pollinator entered\n a flower * Approach - residuals from a linear model of Approach ~ Block,\n taken to remove block effect from the SEM; Approach represents number of\n times within an observing period a pollinator approached, but did not\n enter, a flower * relFit - residuals from a linear model of relFit ~\n Block, taken to remove block effect from the SEM; relFit is relative\n fitness (total seed count divided by mean seed count) * CWresid -\n residuals from a linear model of Corolla Width ~ Block taken to remove\n block effect from the SEM * CLresid - residuals from a linear model of\n Corolla Length ~ Block taken to remove block effect from the SEM *\n ASDresid - residuals from a linear model of ASD ~ Block taken to remove\n block effect from the SEM * Bresid - residuals from a linear model of Brix\n ~ Block taken to remove block effect from the SEM * FFresid - residuals\n from a linear model of Julian Date of First Flower ~ Block taken to remove\n block effect from the SEM * LCresid - residuals from a linear model of\n Leaf Count ~ Block taken to remove block effect from the SEM ##\n Code/Software All analysis and generation of figures included as an R\n markdown file (Full_Code.Rmd). Seven external R scripts are referenced and\n included.","descriptionType":"TechnicalInfo"}],"geoLocations":[],"fundingReferences":[{"schemeUri":"https://ror.org","funderName":"University of Michigan","funderIdentifier":"https://ror.org/00jmfr291","funderIdentifierType":"ROR"}],"url":"https://datadryad.org/dataset/doi:10.5061/dryad.2z34tmpz8","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-06-15T17:23:53Z","registered":"2026-06-15T17:23:54Z","published":null,"updated":"2026-06-15T17:23:54Z"},"relationships":{"client":{"data":{"id":"dryad.dryad","type":"clients"}}}},{"id":"10.25828/vr0p-ch08","type":"dois","attributes":{"doi":"10.25828/vr0p-ch08","identifiers":[],"creators":[{"name":"Angotti, Nicole","nameType":"Personal","givenName":"Nicole","familyName":"Angotti","affiliation":[{"name":"American University","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/052w4zt36","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Clark, Samuel","nameType":"Personal","givenName":"Samuel","familyName":"Clark","affiliation":[{"name":"The Ohio State University","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/00rs6vg23","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Gómez-Olivé, F. Xavier","nameType":"Personal","givenName":"F. Xavier","familyName":"Gómez-Olivé","affiliation":[{"name":"University of the Witwatersrand","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/03rp50x72","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Houle, Brian","nameType":"Personal","givenName":"Brian","familyName":"Houle","affiliation":[{"name":"Australian National University","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/019wvm592","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Whiteson, Chodziwadziwa Kabudula","nameType":"Personal","givenName":"Chodziwadziwa Kabudula","familyName":"Whiteson","affiliation":[{"name":"University of the Witwatersrand","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/03rp50x72","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Menken, Jane","nameType":"Personal","givenName":"Jane","familyName":"Menken","affiliation":[{"name":"University of Colorado Boulder","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/02ttsq026","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Mojola, Sanyu","nameType":"Personal","givenName":"Sanyu","familyName":"Mojola","affiliation":[{"name":"Princeton University","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/00hx57361","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Schatz, Enid","nameType":"Personal","givenName":"Enid","familyName":"Schatz","affiliation":[{"name":"University of Missouri","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/02ymw8z06","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Tilstra, Andrea","nameType":"Personal","givenName":"Andrea","familyName":"Tilstra","affiliation":[{"name":"University of Oxford","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/052gg0110","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Williams, Jill","nameType":"Personal","givenName":"Jill","familyName":"Williams","affiliation":[{"name":"University of Colorado Boulder","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/02ttsq026","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Dlamini, Vusi","nameType":"Personal","givenName":"Vusi","familyName":"Dlamini","affiliation":[{"name":"University of Maryland, College Park","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/047s2c258","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Ice, Erin","nameType":"Personal","givenName":"Erin","familyName":"Ice","affiliation":[{"name":"University of Michigan–Ann Arbor","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]}],"titles":[{"lang":"en","title":"HIV After 40 2010-2019","titleType":null}],"publisher":{"name":"DataFirst"},"container":{},"publicationYear":2022,"subjects":[{"subject":"FOS: Social sciences","schemeUri":"https://web-archive.oecd.org/2012-06-15/138575-38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)","classificationCode":"5"}],"contributors":[],"dates":[],"language":"en","types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[],"relatedItems":[],"sizes":[],"formats":[],"version":"1","rightsList":[{"rights":"Creative Commons Attribution Non Commercial 4.0 International","rightsUri":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-nc-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[],"geoLocations":[{"geoLocationPlace":"South Africa"}],"fundingReferences":[],"url":"https://www.datafirst.uct.ac.za/dataportal/index.php/catalog/911","contentUrl":null,"metadataVersion":6,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"fabricaForm","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2022-09-09T13:16:10Z","registered":"2022-09-09T13:16:10Z","published":null,"updated":"2026-06-13T17:21:36Z"},"relationships":{"client":{"data":{"id":"dafi.client","type":"clients"}}}},{"id":"10.5281/zenodo.20671040","type":"dois","attributes":{"doi":"10.5281/zenodo.20671040","identifiers":[{"identifier":"oai:zenodo.org:20671040","identifierType":"oai"}],"creators":[{"name":"Mehta, Kunal","nameType":"Personal","givenName":"Kunal","familyName":"Mehta","affiliation":[{"name":"University of Michigan","affiliationIdentifier":"edmo:3655","affiliationIdentifierScheme":"OTHER"}],"nameIdentifiers":[{"nameIdentifier":"0009-0008-6318-7630","nameIdentifierScheme":"ORCID"}]},{"name":"De Furio, Matthew","nameType":"Personal","givenName":"Matthew","familyName":"De Furio","affiliation":[{"name":"University of Michigan–Ann Arbor","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"},{"name":"The University of Texas at Austin","affiliationIdentifier":"https://ror.org/00hj54h04","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0003-1863-4960","nameIdentifierScheme":"ORCID"}]},{"name":"Meyer, Michael R.","nameType":"Personal","givenName":"Michael R.","familyName":"Meyer","affiliation":[{"name":"University of Michigan"}],"nameIdentifiers":[{"nameIdentifier":"0000-0003-1227-3084","nameIdentifierScheme":"ORCID"}]},{"name":"Scholz, Aleks","nameType":"Personal","givenName":"Aleks","familyName":"Scholz","affiliation":[{"name":"University of St Andrews","affiliationIdentifier":"https://ror.org/02wn5qz54","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0001-8993-5053","nameIdentifierScheme":"ORCID"}]},{"name":"Reiter, Megan","nameType":"Personal","givenName":"Megan","familyName":"Reiter","affiliation":[{"name":"Rice University","affiliationIdentifier":"https://ror.org/008zs3103","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0002-3887-6185","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"From Stars Towards the Opacity Limit: Probing Dynamical Impacts on Multiplicity in NGC 1333"}],"publisher":{"name":"Zenodo"},"container":{},"publicationYear":2026,"subjects":[{"subject":"multiplicity"},{"subject":"star clusters"},{"subject":"low mass stars"},{"subject":"brown 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Kunal","nameType":"Personal","givenName":"Kunal","familyName":"Mehta","affiliation":[{"name":"University of Michigan","affiliationIdentifier":"edmo:3655","affiliationIdentifierScheme":"OTHER"}],"nameIdentifiers":[{"nameIdentifier":"0009-0008-6318-7630","nameIdentifierScheme":"ORCID"}]},{"name":"De Furio, Matthew","nameType":"Personal","givenName":"Matthew","familyName":"De Furio","affiliation":[{"name":"University of Michigan–Ann Arbor","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"},{"name":"The University of Texas at Austin","affiliationIdentifier":"https://ror.org/00hj54h04","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0003-1863-4960","nameIdentifierScheme":"ORCID"}]},{"name":"Meyer, Michael R.","nameType":"Personal","givenName":"Michael R.","familyName":"Meyer","affiliation":[{"name":"University of Michigan"}],"nameIdentifiers":[{"nameIdentifier":"0000-0003-1227-3084","nameIdentifierScheme":"ORCID"}]},{"name":"Scholz, Aleks","nameType":"Personal","givenName":"Aleks","familyName":"Scholz","affiliation":[{"name":"University of St Andrews","affiliationIdentifier":"https://ror.org/02wn5qz54","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0001-8993-5053","nameIdentifierScheme":"ORCID"}]},{"name":"Reiter, Megan","nameType":"Personal","givenName":"Megan","familyName":"Reiter","affiliation":[{"name":"Rice University","affiliationIdentifier":"https://ror.org/008zs3103","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0002-3887-6185","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"From Stars Towards the Opacity Limit: Probing Dynamical Impacts on Multiplicity in NGC 1333"}],"publisher":{"name":"Zenodo"},"container":{},"publicationYear":2026,"subjects":[{"subject":"multiplicity"},{"subject":"star clusters"},{"subject":"low mass stars"},{"subject":"brown dwarfs"},{"subject":"dynamics"}],"contributors":[],"dates":[{"date":"2026-06-12","dateType":"Issued"},{"date":"2026-06-12","dateType":"Submitted"}],"language":null,"types":{"ris":"RPRT","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"Poster","resourceTypeGeneral":"Text"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20671039","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20671039","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":1,"versionOfCount":1,"created":"2026-06-13T01:52:47Z","registered":"2026-06-13T01:52:47Z","published":null,"updated":"2026-06-13T01:52:47Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5061/dryad.jwstqjqpc","type":"dois","attributes":{"doi":"10.5061/dryad.jwstqjqpc","identifiers":[],"creators":[{"name":"Morgan, Thomas","nameType":"Personal","givenName":"Thomas","familyName":"Morgan","affiliation":[{"name":"University of Michigan","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3610-8764","nameIdentifierScheme":"ORCID"}]},{"name":"Alofs, Karen","nameType":"Personal","givenName":"Karen","familyName":"Alofs","affiliation":[{"name":"University of Michigan","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Taphorn, Don","nameType":"Personal","givenName":"Don","familyName":"Taphorn","affiliation":[{"name":"University of Michigan","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Hemraj-Naraine, Devya","nameType":"Personal","givenName":"Devya","familyName":"Hemraj-Naraine","affiliation":[{"name":"University of Guyana","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/05d8pm274","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Liverpool, Elford","nameType":"Personal","givenName":"Elford","familyName":"Liverpool","affiliation":[{"name":"University of Guyana","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/05d8pm274","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Mol, Jan","nameType":"Personal","givenName":"Jan","familyName":"Mol","affiliation":[{"name":"Anton de Kom University of Suriname","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/02m8qhj08","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Covain, Raphael","nameType":"Personal","givenName":"Raphael","familyName":"Covain","affiliation":[{"name":"Natural History Museum of Geneva","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/03ftcjb67","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-8186-8914","nameIdentifierScheme":"ORCID"}]},{"name":"Lujan, Nathan","nameType":"Personal","givenName":"Nathan","familyName":"Lujan","affiliation":[{"name":"Royal Ontario Museum","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/00vcj2z66","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"López-Fernández, Hernán","nameType":"Personal","givenName":"Hernán","familyName":"López-Fernández","affiliation":[{"name":"University of Michigan","schemeUri":"https://ror.org","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0270-1671","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Data from: Dispersal across headwaters determines fish population structure between interdigitating river systems in the Guiana Shield highlands"}],"publisher":{"name":"Dryad","schemeUri":"https://ror.org/","publisherIdentifier":"https://ror.org/00x6h5n95","publisherIdentifierScheme":"ROR"},"container":{},"publicationYear":2026,"subjects":[{"subject":"FOS: Natural sciences","schemeUri":"https://web-archive.oecd.org/2012-06-15/138575-38235147.pdf","subjectScheme":"fos"},{"subject":"FOS: Natural sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Population genetics","schemeUri":"https://github.com/PLOS/plos-thesaurus","subjectScheme":"PLOS Subject Area Thesaurus"},{"subject":"Aquatic environments","schemeUri":"https://github.com/PLOS/plos-thesaurus","subjectScheme":"PLOS Subject Area Thesaurus"},{"subject":"Fish","schemeUri":"https://github.com/PLOS/plos-thesaurus","subjectScheme":"PLOS Subject Area Thesaurus"},{"subject":"Biogeography","schemeUri":"https://github.com/PLOS/plos-thesaurus","subjectScheme":"PLOS Subject Area Thesaurus"},{"subject":"Phylogenetics","schemeUri":"https://github.com/PLOS/plos-thesaurus","subjectScheme":"PLOS Subject Area Thesaurus"},{"subject":"Phylogeography","schemeUri":"https://github.com/PLOS/plos-thesaurus","subjectScheme":"PLOS Subject Area Thesaurus"},{"subject":"Rivers","schemeUri":"https://github.com/PLOS/plos-thesaurus","subjectScheme":"PLOS Subject Area Thesaurus"}],"contributors":[],"dates":[{"date":"2025-10-08T14:19:56Z","dateType":"Created"},{"date":"2026-05-19T00:48:14Z","dateType":"Submitted"},{"date":"2026-06-13T00:00:00Z","dateType":"Issued"},{"date":"2026-06-13T00:00:00Z","dateType":"Available"}],"language":"en","types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","relatedIdentifier":"10.1002/ece3.73603","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["48241966897 bytes"],"formats":[],"version":"9","rightsList":[{"rights":"Creative Commons Zero v1.0 Universal","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc0-1.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Riverine aquatic species primarily occupy the dendritic networks that\n define river basins, and population-structure models for riverine taxa,\n including freshwater fishes, generally assume strictly longitudinal\n dispersal within these networks. River configurations, however, are\n dynamic: hydrologic connections change seasonally and over geologic time,\n potentially enabling out-of-network dispersal, a process that remains\n poorly studied. Because such dispersal violates key assumptions of\n existing models, its prevalence may require the development of new\n frameworks for understanding riverine population structure. To test for\n out-of-network connectivity between interdigitating river systems, we\n analyzed genetic population structure in Krobia potaroensis, a cichlid\n fish endemic to the rivers draining the Pakaraima Mountains in western\n Guyana, South America. We detected genetic associations among populations\n that do not correspond to contemporary river configurations, indicating\n historical or ongoing dispersal between adjacent river systems. These\n results demonstrate that within-network longitudinal dispersal cannot\n always be assumed and that alternative dispersal routes can shape\n population structure, genetic diversity, and genetic differentiation in\n riverine taxa.","descriptionType":"Abstract"},{"description":"# Data from: Dispersal across headwaters determines fish population\n structure between interdigitating river systems in the Guiana Shield\n highlands Dataset DOI:\n [10.5061/dryad.jwstqjqpc](https://doi.org/10.5061/dryad.jwstqjqpc) Genomic\n (RADseq) data for Krobia species (subfamily Cichlinae). Each sample has\n two associated fastq files, derived matrices are also included, as well as\n metadata for each individual. ## Description of the data and file\n structure Double digest RADseq data (RAW fastq and derived sequence\n matrices) for 79 Krobia individuals (Subfamily: Cichlinae) from across the\n Guianas of South America. Files are separated by individual with file\n names corresponding to metadata in the associated text files. Dataset\n corresponds to a phylogenetic dataset with broader representation of\n fishes within the genus (n=79), and more focused dataset that corresponds\n to fishes from within the rivers of the Pakaraima Mountains of western\n Guyana (n=63 and n=59). The data was used for phylogenetic analyses and\n population genetic analyses across a set of putatively disconnected river\n systems. The analyses and interpretations are further detailed in Morgan\n et al. (2026), Ecology and Evolution 16 (5), e73603. Each individual\n (fish) has two FASTQ files (R1 \u0026amp; R2) corresponding to PE150 Illumina\n sequencing. From these raw files, as well as various output matrices\n generated by ipyrad. Files were generated with default parameters in\n ipyrad, but with a 0.85 clustering threshold, a minimum depth of 6 per\n locus. Each sequence/SNP-matrix was then generated using different\n thresholds for line 21 in the ipyrad params file\n \"[min_samples_locus]\". The minimum number of samples per\n included locus in the matrix is indicated in the file name for each\n matrix: e.g. \"45of59\" indicates a file that has data for 59\n individuals with all loci that were present in at least 45 of those\n individuals (\u0026gt;75% in this example). Ipyrad then outputs the same\n dataset in multiple common formats (e.g. \".str\" for STRUCTURE;\n Pritchard et al. 2000) ### Files+folders Files zipped within\n `Data-for-dryad-Morgan-et-al-2026-Pakaraimas.zip` *\n \"Demultiplexed-sequences\": Folder containing raw fastq files, as\n described above and in Table S1. * \"ipyrad-output\": Folder\n containing ipyrad outputs. Various SNP and sequence matrices. Three runs\n of ipyrad were used to generate these outputs. Default parameters were\n used in ipyrad, but with 0.85 clustering threshold and a minimum depth of\n 6. The differing matrices were generated by altering the number of samples\n included and the minimum number of individuals that needed to have the\n locus for it to be included (Line 21 in the parameters file).\n `Table-S1-Morgan-et-al-2026-sample-details.csv` - Sample naming\n conventions, GPS coordinates, Species identities. ** indicate two samples\n originally listed as 'Kuri' (Kuribrong) are from within the\n Potaro River. `TableS2-Pakaraimas-loci-stats-2026.csv` - genotype data\n stats for each individual after fastqs have been processed through\n ipyrad.  ## Code/software The FASTQ files can be processed as in the\n manuscript using ipyrad (Eaton and Overcast 2020), but can be processed by\n any of the typical RADseq or alignment pipelines. Csv files containing\n sample information can be viewed in any text editor or spreadsheet\n software. ## References Eaton, D. A. R., \u0026amp; Overcast, I. (2020).\n ipyrad: Interactive assembly and analysis of RADseq datasets.\n Bioinformatics, 36(8), 2592–2594.\n [https://doi.org/10.1093/bioinformatics/btz966](https://doi.org/10.1093/bioinformatics/btz966) Pritchard, J. K., Stephens, M., \u0026amp; Donnelly, P. (2000). Inference of Population Structure Using Multilocus Genotype Data. Genetics, 155(2), 945–959.","descriptionType":"TechnicalInfo"}],"geoLocations":[],"fundingReferences":[{"schemeUri":"https://ror.org","funderName":"Natural Sciences and Engineering Research Council of Canada","funderIdentifier":"https://ror.org/01h531d29","funderIdentifierType":"ROR"}],"url":"https://datadryad.org/dataset/doi:10.5061/dryad.jwstqjqpc","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-06-13T00:02:09Z","registered":"2026-06-13T00:02:10Z","published":null,"updated":"2026-06-13T00:02:10Z"},"relationships":{"client":{"data":{"id":"dryad.dryad","type":"clients"}}}},{"id":"10.5281/zenodo.20649687","type":"dois","attributes":{"doi":"10.5281/zenodo.20649687","identifiers":[{"identifier":"oai:zenodo.org:20649687","identifierType":"oai"}],"creators":[{"name":"Chenoweth, Megan","nameType":"Personal","givenName":"Megan","familyName":"Chenoweth","affiliation":[{"name":"University of Michigan–Ann Arbor","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"},{"name":"Inter-university Consortium for Political and Social Research","affiliationIdentifier":"https://ror.org/02q7mkh03","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0001-6434-7722","nameIdentifierScheme":"ORCID"}]},{"name":"Lyle, Jared","nameType":"Personal","givenName":"Jared","familyName":"Lyle","affiliation":[{"name":"Inter-university Consortium for Political and Social Research","affiliationIdentifier":"https://ror.org/02q7mkh03","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0001-8623-7612","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Enhancing ICPSR's Subject Thesaurus For The Artificial Intelligence Era"}],"publisher":{"name":"Zenodo"},"container":{},"publicationYear":2026,"subjects":[{"subject":"Controlled vocabulary"},{"subject":"Subject thesaurus"},{"subject":"Artificial intelligence"},{"subject":"Data discovery"}],"contributors":[],"dates":[{"date":"2026-06-04","dateType":"Issued"}],"language":"en","types":{"ris":"RPRT","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"Presentation","resourceTypeGeneral":"Text"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20649686","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"A subject thesaurus is a controlled vocabulary that describes information resources using standardized language and hierarchical relationships between concepts. Consistent terms guide users toward preferred terminology, reduce ambiguity, and enable reliable searching and filtering across large collections.In 1999-2003, ICPSR created a thesaurus of social science terms and applied those terms to its data resources. The ICPSR subject thesaurus has grown and been maintained since that time, but not always consistently. New terms have been added as needed and not applied retroactively. Subject terms from outside the thesaurus appear in many studies, most self-published. Efforts to align the subject thesaurus with other controlled vocabularies, such as Library of Congress Subject Headings, are hampered by differences in structure and context.While research on ICPSR’s data curation practices has suggested that subject terms contribute significantly to usage, improvements in artificial intelligence raise questions about the best uses for subject thesauri in the context of large language models.ICPSR is attempting to refine and modernize our subject thesaurus to maximize its relevance in the AI discovery environment. Our first step in this process is to explore the current state of the thesaurus and how it has changed over time. We’ll share early findings from this project, looking at things like: number of subject terms; distribution of terms across studies; comparison between most-used and most-searched terms; hierarchical relationships between terms (broader, narrower, preferred, and related terms); and potentially, semantic relationships between terms (topical clustering).Additionally, we’ll touch on the role of subject thesauri in the age of AI. How can controlled vocabularies be integrated into AI-driven discovery systems? What do LLMs do better than thesauri, and when are thesauri the most useful? Our findings will inform improvements to the ICPSR subject thesaurus, with potential applications to other repositories facing similar challenges.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20649687","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-06-12T18:52:19Z","registered":"2026-06-12T18:52:19Z","published":null,"updated":"2026-06-12T18:52:19Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20649686","type":"dois","attributes":{"doi":"10.5281/zenodo.20649686","identifiers":[],"creators":[{"name":"Chenoweth, Megan","nameType":"Personal","givenName":"Megan","familyName":"Chenoweth","affiliation":[{"name":"University of Michigan–Ann Arbor","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"},{"name":"Inter-university Consortium for Political and Social Research","affiliationIdentifier":"https://ror.org/02q7mkh03","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0001-6434-7722","nameIdentifierScheme":"ORCID"}]},{"name":"Lyle, Jared","nameType":"Personal","givenName":"Jared","familyName":"Lyle","affiliation":[{"name":"Inter-university Consortium for Political and Social Research","affiliationIdentifier":"https://ror.org/02q7mkh03","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"nameIdentifier":"0000-0001-8623-7612","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Enhancing ICPSR's Subject Thesaurus For The Artificial Intelligence Era"}],"publisher":{"name":"Zenodo"},"container":{},"publicationYear":2026,"subjects":[{"subject":"Controlled vocabulary"},{"subject":"Subject thesaurus"},{"subject":"Artificial intelligence"},{"subject":"Data discovery"}],"contributors":[],"dates":[{"date":"2026-06-04","dateType":"Issued"}],"language":"en","types":{"ris":"RPRT","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"Presentation","resourceTypeGeneral":"Text"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20649686","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"A subject thesaurus is a controlled vocabulary that describes information resources using standardized language and hierarchical relationships between concepts. Consistent terms guide users toward preferred terminology, reduce ambiguity, and enable reliable searching and filtering across large collections.In 1999-2003, ICPSR created a thesaurus of social science terms and applied those terms to its data resources. The ICPSR subject thesaurus has grown and been maintained since that time, but not always consistently. New terms have been added as needed and not applied retroactively. Subject terms from outside the thesaurus appear in many studies, most self-published. Efforts to align the subject thesaurus with other controlled vocabularies, such as Library of Congress Subject Headings, are hampered by differences in structure and context.While research on ICPSR’s data curation practices has suggested that subject terms contribute significantly to usage, improvements in artificial intelligence raise questions about the best uses for subject thesauri in the context of large language models.ICPSR is attempting to refine and modernize our subject thesaurus to maximize its relevance in the AI discovery environment. Our first step in this process is to explore the current state of the thesaurus and how it has changed over time. We’ll share early findings from this project, looking at things like: number of subject terms; distribution of terms across studies; comparison between most-used and most-searched terms; hierarchical relationships between terms (broader, narrower, preferred, and related terms); and potentially, semantic relationships between terms (topical clustering).Additionally, we’ll touch on the role of subject thesauri in the age of AI. How can controlled vocabularies be integrated into AI-driven discovery systems? What do LLMs do better than thesauri, and when are thesauri the most useful? Our findings will inform improvements to the ICPSR subject thesaurus, with potential applications to other repositories facing similar challenges.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20649686","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-06-12T18:52:19Z","registered":"2026-06-12T18:52:19Z","published":null,"updated":"2026-06-12T18:52:19Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.25921/kbqy-4v05","type":"dois","attributes":{"doi":"10.25921/kbqy-4v05","identifiers":[],"creators":[{"name":"Sulpis, Olivier","nameType":"Personal","givenName":"Olivier","familyName":"Sulpis","affiliation":[{"name":"McGill University","schemeUri":"https://ror.org/","affiliationIdentifier":"https://ror.org/01pxwe438","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-6463-3320","nameIdentifierScheme":"ORCID"}]},{"name":"Boudreau, Bernard P.","nameType":"Personal","givenName":"Bernard P.","familyName":"Boudreau","affiliation":[{"name":"Dalhousie University; Institute of Oceanography"}],"nameIdentifiers":[]},{"name":"Mucci, Alfonso","nameType":"Personal","givenName":"Alfonso","familyName":"Mucci","affiliation":[{"name":"McGill University","schemeUri":"https://ror.org/","affiliationIdentifier":"https://ror.org/01pxwe438","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Jenkins, Chris","nameType":"Personal","givenName":"Chris","familyName":"Jenkins","affiliation":[{"name":"University of Colorado Boulder","schemeUri":"https://ror.org/","affiliationIdentifier":"https://ror.org/02ttsq026","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Trossman, David S.","nameType":"Personal","givenName":"David S.","familyName":"Trossman","affiliation":[{"name":"The University of Texas at Austin (UT Austin)","schemeUri":"https://ror.org/","affiliationIdentifier":"https://ror.org/00hj54h04","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Arbic, Brian K.","nameType":"Personal","givenName":"Brian K.","familyName":"Arbic","affiliation":[{"name":"University of Michigan","schemeUri":"https://ror.org/","affiliationIdentifier":"https://ror.org/00jmfr291","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]},{"name":"Key, Robert M.","nameType":"Personal","givenName":"Robert M.","familyName":"Key","affiliation":[{"name":"Princeton University","schemeUri":"https://ror.org/","affiliationIdentifier":"https://ror.org/00hx57361","affiliationIdentifierScheme":"ROR"}],"nameIdentifiers":[]}],"titles":[{"title":"Current calcite (CaCO3) dissolution at the seafloor caused by anthropogenic CO2 (NCEI Accession 0176672)"}],"publisher":{"lang":"en","name":"NOAA National Centers for Environmental Information","schemeUri":"https://ror.org/","publisherIdentifier":"https://ror.org/04r0wrp59","publisherIdentifierScheme":"ROR"},"container":{},"publicationYear":2018,"subjects":[],"contributors":[],"dates":[{"date":"2018","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[],"descriptions":[{"description":"This dataset consists of current CaCO3 dissolution at the seafloor caused by anthropogenic CO2 in the World Oceans. This dataset contains the main results from Sulpis et al. (PNAS, 2018). All the variables have a 1x1 degree resolution. It can be used to compute calcite dissolution at the seafloor for changing bottom-water chemistry, calcite rain rates or current speeds, for instance. Oceanic uptake of anthropogenic CO2 leads to decreased pH, carbonate ion concentration, and saturation state with respect to CaCO3 minerals, causing increased dissolution of these minerals at the deep seafloor. This additional dissolution will figure prominently in the neutralization of man-made CO2. Yet, there has been no concerted assessment of the current extent of anthropogenic CaCO3 dissolution at the deep seafloor. Here, recent databases of bottom-water chemistry, benthic currents, and CaCO3 content of deep-sea sediments are combined with a new rate model to derive the global distribution of benthic calcite dissolution rates and obtain primary confirmation of an anthropogenic component. By comparing pre-industrial with present-day rates, we determine that significant anthropogenic dissolution now occurs in the western North Atlantic, amounting to 40-100% of the total seafloor dissolution at its most intense locations. At these locations, the calcite compensation depth has risen ~300 m. Increased benthic dissolution was also revealed at various hot spots in the southern extent of the Atlantic, Indian and Pacific Oceans. Our findings place constraints on future predictions of ocean acidification, are consequential to the fate of benthic calcifiers, and indicate that a by-product of human activities is currently altering the geological record of the deep 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Although exact in principle, in practice, it relies on approximations to the exchange-correlation (XC) functional, which is known to be a unique functional of the electron density. Despite 50 years of active research, existing XC approximations remain far from general purpose chemical accuracy of various thermochemical and materials properties. In that light, the inverse DFT problem, of finding the exact XC potential corresponding to an accurate groundstate density, offers an insightful tool to understand the nature of the XC functional as well as aid in the development of more accurate functionals. However, solving the inverse DFT problem is fraught with several numerical challenges, such as non-uniqueness or spurious oscillations in the solution and non-convergence. We present invDFT as an open-source framework to address the outstanding challenges in inverse DFT and computed XC potentials solely from a target density. We do so by use of a systematically convergent differential finite-element basis—higher-order finite-elements for the Kohn-Sham orbitals and linear finite-elements for the XC potential—which together render the inverse DFT problem well-posed. We also employ necessary asymptotic corrections to the target density to avoid any unphysical oscillations in the resulting XC potential. We also employ several numerical and high-performance computing (HPC) advances that affords both efficiency and parallel scalability, on CPU-GPU hybrid architectures. 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This dataset consists of acoustic and acceleration data for extracted and labelled calls from 12 animals in 5 social groups (3 pairs and 2 groups of 3), concatenated data tables, and the code used to label calls, extract features, and combine data tables. ","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[{"awardTitle":"Living Marine Resources grant","funderName":"United States Navy","awardNumber":"N3943023C2502","funderIdentifier":"10.13039/100009896","funderIdentifierType":"Crossref Funder ID"},{"awardTitle":"Living Marine Resources grant","funderName":"United States Navy","awardNumber":"N3943022C2413","funderIdentifier":"10.13039/100009896","funderIdentifierType":"Crossref Funder ID"},{"awardTitle":"Volgenau Foundation","funderName":"Stellwagen Bank National Marine 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