cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0191270.10fu
title: SH0191270.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0191271.10fu
title: SH0191271.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0191272.10fu
title: SH0191272.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3886/e242805
title: Weekly Cumulative RSV Vaccination Coverage and Intent, Overall, by Selected Demographics and Jurisdiction, Among Adults 75 and Older and 60-74 Years with High-Risk Conditions Ever Vaccinated, United States

description: Weekly Cumulative RSV Vaccination Coverage and Intent Among Adults 75 Years and Older and 6074 Years with High Risk Conditions Ever Vaccinated with RSV Vaccine by Demographic Characteristics and Jurisdiction

 Weekly estimates of RSV vaccination coverage and intent among adults 75 years and older and 6074 years with high risk conditions are calculated using data from the National Immunization SurveyAdult COVID Module (NISACM) (https://www.cdc.gov/nis/about/index.html).

 In June 2023, the Advisory Committee on Immunization Practices (ACIP) voted to recommend that adults aged 60 years may receive a single dose of an RSV vaccine, using shared clinical decision-making. In June 2024, the ACIP voted to recommend a single dose of RSV vaccine for all adults 75 years and older and adults 6074 years who are at increased risk for severe RSV disease. The data below captures ever receiving a dose of an RSV vaccine by adults 60 years and older.
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description: (Downloaded 1/7/2026)
DOI: 10.15156/bio/sh0191273.10fu
title: SH0191273.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3886/e242805v1
title: Weekly Cumulative RSV Vaccination Coverage and Intent, Overall, by Selected Demographics and Jurisdiction, Among Adults 75 and Older and 60-74 Years with High-Risk Conditions Ever Vaccinated, United States

description: Weekly Cumulative RSV Vaccination Coverage and Intent Among Adults 75 Years and Older and 6074 Years with High Risk Conditions Ever Vaccinated with RSV Vaccine by Demographic Characteristics and Jurisdiction

 Weekly estimates of RSV vaccination coverage and intent among adults 75 years and older and 6074 years with high risk conditions are calculated using data from the National Immunization SurveyAdult COVID Module (NISACM) (https://www.cdc.gov/nis/about/index.html).

 In June 2023, the Advisory Committee on Immunization Practices (ACIP) voted to recommend that adults aged 60 years may receive a single dose of an RSV vaccine, using shared clinical decision-making. In June 2024, the ACIP voted to recommend a single dose of RSV vaccine for all adults 75 years and older and adults 6074 years who are at increased risk for severe RSV disease. The data below captures ever receiving a dose of an RSV vaccine by adults 60 years and older.
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description: (Downloaded 1/7/2026)
DOI: 10.15156/bio/sh0191274.10fu
title: SH0191274.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0191275.10fu
title: SH0191275.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0191276.10fu
title: SH0191276.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0191277.10fu
title: SH0191277.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0191278.10fu
title: SH0191278.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.14837889
title: Avidity Index Analysis and Regularization Model for Pre-DENV2 Sera Post-Primary ZIKV Infection

description: This dataset and code pertain to the avidity index analysis of IgG and IgA antibodies in pre-infection sera from individuals with a prior primary Zika virus (ZIKV) infection and before a subsequent dengue virus 2 infection (Fig. 1D and fig S1B). The dataset includes avidity measurements for IgG, IgA, and combined IgG+IgA responses targeting E, EDIII and NS1. The accompanying code implements a regularization model to assess the classification performance of antibody avidity.
DOI: 10.5281/zenodo.14837882
title: Antibody Profiling and Regularization Model for Pre-Secondary DENV2 Sera Post-Primary ZIKV Infection – Pediatric Dengue Cohort

description: This dataset contains antibody profiling of serum samples from the Pediatric Dengue Cohort Study, collected after a primary Zika virus (ZIKV) infection and before a secondary DENV2 infection (Fig 1B, C and fig S1A). It includes quantitative measurements of multiple antibody isotypes (Total IgG, IgG1, IgG2, IgG3, IgG4, IgA, and IgM) across three antigenic targets (E, EDIII, and NS1). Accompanying this dataset, the code implements a regularization model for coefficient adjustment.
DOI: 10.5281/zenodo.14837883
title: Antibody Profiling and Regularization Model for Pre-Secondary DENV2 Sera Post-Primary ZIKV Infection – Pediatric Dengue Cohort

description: This dataset contains antibody profiling of serum samples from the Pediatric Dengue Cohort Study, collected after a primary Zika virus (ZIKV) infection and before a secondary DENV2 infection (Fig 1B, C and fig S1A). It includes quantitative measurements of multiple antibody isotypes (Total IgG, IgG1, IgG2, IgG3, IgG4, IgA, and IgM) across three antigenic targets (E, EDIII, and NS1). Accompanying this dataset, the code implements a regularization model for coefficient adjustment.
DOI: 10.5281/zenodo.14840019
title: unimpeded: nlcdm bao.sdss_dr16+sn.pantheon

description: cosmological model:nlcdm, dataset:bao.sdss_dr16+sn.pantheon
DOI: 10.5281/zenodo.14840020
title: unimpeded: nlcdm bao.sdss_dr16+sn.pantheon

description: cosmological model:nlcdm, dataset:bao.sdss_dr16+sn.pantheon
DOI: 10.5281/zenodo.14839628
title: unimpeded: klcdm planck_2018_CamSpec_nolens+sn.pantheon

description: cosmological model:klcdm, dataset:planck_2018_CamSpec_nolens+sn.pantheon
DOI: 10.5281/zenodo.14839629
title: unimpeded: klcdm planck_2018_CamSpec_nolens+sn.pantheon

description: cosmological model:klcdm, dataset:planck_2018_CamSpec_nolens+sn.pantheon
DOI: 10.2908/hlth_silc_09c
title: Persons reporting needs for dental examination or treatment by sex, age and at risk of poverty and social exclusion situation
title: Personnes signalant des besoins d'examen ou de traitement dentaire par sexe, âge et situation de risque de pauvreté et d'exclusion sociale
title: Personen, die Bedarf an zahnärztlicher Untersuchung oder Behandlung melden, nach Geschlecht, Alter und Armuts- sowie sozialer Ausgrenzungsgefährdung
DOI: 10.2908/hlth_silc_08c
title: Persons reporting needs for medical examination or treatment by sex, age and at risk of poverty and social exclusion situation
title: Personnes signalant des besoins d'examen ou de traitement médical par sexe, âge et situation de risque de pauvreté et d'exclusion sociale
title: Personen, die Bedarf an medizinischer Untersuchung oder Behandlung melden, nach Geschlecht, Alter und Armuts- sowie sozialer Ausgrenzungsgefährdung
DOI: 10.15468/xh78d2
title: Checklist of alien mammals of Belgium

description: The checklist of alien mammals of Belgium is a species checklist dataset published by the Research Institute for Nature and Forest (INBO). It contains information on alien mammal species recorded in the wild in Belgium since 1976. Both established species and occasional records (casuals) are included, but with information on the degree of establishment of species following the unified invasion framework of Blackburn et al. (2011). The checklist is published here as a standardized Darwin Core Archive and includes for each (sub)species: the scientific name and classification (in the taxon core), the presence in Flanders, Wallonia and the Brussels-Capital Region, year of first and last observation in Belgium, the degree of establishment and pathway(s) of introduction (in the distribution extension), coarse habitat information (in the species profile extension), and native range(s) (in the description extension). A reference (scientific, gray literature, online source) to this information is provided. Issues with the dataset can be reported at https://github.com/trias-project/alien-mammals-checklist/issues.
We have released this dataset to the public domain under a Creative Commons Zero waiver. We would appreciate it if you follow the GBIF citation guidelines (https://www.gbif.org/citation-guidelines) when using the data. If you have any questions regarding this dataset, don’t hesitate to contact us via the contact information provided in the metadata.
This dataset was published as open data for the TrIAS project (Tracking Invasive Alien Species http://trias-project.be, Vanderhoeven et al. 2017), with technical support provided by the Research Institute for Nature and Forest (INBO). It is selected as one of the authoritative sources for the compilation of a unified and reproducible checklist of alien species in Belgium (GRIIS Belgium, Desmet et al. 2023).
DOI: 10.15468/7q6weq
title: Checklist of alien mammals of Belgium

description: The checklist of alien mammals of Belgium is a species checklist dataset published by the Research Institute for Nature and Forest (INBO). It contains information on alien mammal species recorded in the wild in Belgium since 1976. Both established species and occasional records (casuals) are included, but with information on the degree of establishment of species following the unified invasion framework of Blackburn et al. (2011). The checklist is published here as a standardized Darwin Core Archive and includes for each (sub)species: the scientific name and classification (in the taxon core), the presence in Flanders, Wallonia and the Brussels-Capital Region, year of first and last observation in Belgium, the degree of establishment and pathway(s) of introduction (in the distribution extension), coarse habitat information (in the species profile extension), and native range(s) (in the description extension). A reference (scientific, gray literature, online source) to this information is provided. Issues with the dataset can be reported at https://github.com/trias-project/alien-mammals-checklist/issues.
We have released this dataset to the public domain under a Creative Commons Zero waiver. We would appreciate it if you follow the GBIF citation guidelines (https://www.gbif.org/citation-guidelines) when using the data. If you have any questions regarding this dataset, don’t hesitate to contact us via the contact information provided in the metadata.
This dataset was published as open data for the TrIAS project (Tracking Invasive Alien Species http://trias-project.be, Vanderhoeven et al. 2017), with technical support provided by the Research Institute for Nature and Forest (INBO). It is selected as one of the authoritative sources for the compilation of a unified and reproducible checklist of alien species in Belgium (GRIIS Belgium, Desmet et al. 2023).
DOI: 10.15468/dl.gbrbqv
title: Occurrence Download

description: A dataset containing 104 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 {
 "or" : [
 "Country is Angola",
 "Country is Bahrain",
 "Country is Benin",
 "Country is Cameroon",
 "Country is Comoros",
 "Country is Congo",
 "Country is Congo, Democratic Republic of the",
 "Country is Côte d’Ivoire",
 "Country is Djibouti",
 "Country is Egypt",
 "Country is Eritrea",
 "Country is Equatorial Guinea",
 "Country is Gabon",
 "Country is Gambia",
 "Country is Ghana",
 "Country is Guinea",
 "Country is Guinea-Bissau",
 "Country is Iran (Islamic Republic of)",
 "Country is Iraq",
 "Country is Jordan",
 "Country is Kenya",
 "Country is Kuwait",
 "Country is Liberia",
 "Country is Madagascar",
 "Country is Mauritania",
 "Country is Mauritius",
 "Country is Mozambique",
 "Country is Nigeria",
 "Country is Oman",
 "Country is Qatar",
 "Country is Réunion",
 "Country is Saudi Arabia",
 "Country is Senegal",
 "Country is Seychelles",
 "Country is Sierra Leone",
 "Country is Somalia",
 "Country is South Africa",
 "Country is South Sudan",
 "Country is Sudan",
 "Country is Tanzania, United Republic of",
 "Country is Togo",
 "Country is United Arab Emirates",
 "Country is Yemen",
 "Country is Zambia",
 "Country is Zimbabwe"
 ]
 },
 "TaxonKey is Acrostichum speciosum Willd.",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 },
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (VAGRANT)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 {
 "not" : {
 "DegreeOfEstablishment" : [
 "is one of (CULTIVATED)"
 ]
 }
 },
 "DegreeOfEstablishment is null"
 ]
 }
 ]
}

 The dataset includes 104 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022728-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14840023
title: unimpeded: Nlcdm bao.sdss_dr16+bicep_keck_2018

description: cosmological model:Nlcdm, dataset:bao.sdss_dr16+bicep_keck_2018
DOI: 10.5281/zenodo.14840024
title: unimpeded: Nlcdm bao.sdss_dr16+bicep_keck_2018

description: cosmological model:Nlcdm, dataset:bao.sdss_dr16+bicep_keck_2018
DOI: 10.15468/dl.u4hkbq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year is greater than or equal to 1981",
 "Year is less than or equal to 2010",
 "HasCoordinate is true",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "VerbatimScientificName is Criptogramma crispa",
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022729-250127130748423/datasets/export for details.
DOI: 10.25976/zfhp-se57
title: Tracking down pharmaceutical pollution in surface waters of the St. Lawrence River and its major tributaries

description: A reconnaissance survey was undertaken to evaluate the occurrence and risks of 27 pharmaceuticals and metabolites in the St. Lawrence watershed.
description: Surface water samples were collected over a five-year period (2017–2021) along a 700-km reach of the St. Lawrence River as well as 55 tributary rivers (overall N = 406 samples). Additionally, depth water samples and sediments were collected near a major wastewater effluent.
DOI: 10.6084/m9.figshare.28382051
title: DesikanKillianyTourvilleOuter.h5

description: DKT weights FOV increase
DOI: 10.6084/m9.figshare.28382051.v1
title: DesikanKillianyTourvilleOuter.h5

description: DKT weights FOV increase