cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1218533.10fu
title: SH1218533.10FU

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/sh1218534.10fu
title: SH1218534.10FU

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/sh1218535.10fu
title: SH1218535.10FU

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/sh1218537.10fu
title: SH1218537.10FU

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/sh1218540.10fu
title: SH1218540.10FU

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/sh1218541.10fu
title: SH1218541.10FU

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/sh1218542.10fu
title: SH1218542.10FU

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/sh1218543.10fu
title: SH1218543.10FU

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: 10.15468/dl.ah4dnc
title: Occurrence Download

description: A dataset containing 507 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hoolock hoolock"
 ]
}

 The dataset includes 507 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012269-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29344775.v4
title: MirtronDB_version2

description: MirtronDB_version2 database dump
DOI: 10.3886/e237010
title: Data and Code for: "Temporary Layoffs, Loss-of-Recall, and Cyclical Unemployment Dynamics"

description: We revisit the role of temporary layoffs in the business cycle. While some have emphasized a stabilizing effect due to recall hiring, we quantify from the data an important countercyclical destabilizing effect due to "loss-of-recall'', whereby workers in temporary-layoff unemployment lose their job permanently. We develop a quantitative model allowing for endogenous flows of workers across employment and both temporary-layoff and jobless unemployment. The model captures both pre- and post-pandemic unemployment dynamics, including the recessionary role of loss-of-recall. We use our structural model to show that the Paycheck Protection program generated sizable employment gains, in part by significantly reducing loss-of-recall.<br><br><br>
DOI: 10.15468/dl.2m2j7p
title: Occurrence Download

description: A dataset containing 4257 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Hedychium coronarium"
 ]
}

 The dataset includes 4257 records from 334 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012266-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e237010v1
title: Data and Code for: "Temporary Layoffs, Loss-of-Recall, and Cyclical Unemployment Dynamics"

description: We revisit the role of temporary layoffs in the business cycle. While some have emphasized a stabilizing effect due to recall hiring, we quantify from the data an important countercyclical destabilizing effect due to "loss-of-recall'', whereby workers in temporary-layoff unemployment lose their job permanently. We develop a quantitative model allowing for endogenous flows of workers across employment and both temporary-layoff and jobless unemployment. The model captures both pre- and post-pandemic unemployment dynamics, including the recessionary role of loss-of-recall. We use our structural model to show that the Paycheck Protection program generated sizable employment gains, in part by significantly reducing loss-of-recall.<br><br><br>
DOI: 10.5519/qd.f32mvwp8
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.15468/dl.rjx3qa
title: Occurrence Download

description: A dataset containing 192 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (hymenoptera, J. B. Wallis / R. E. Roughley Museum of Entomology, LACM Entomology Collection, Frost Entomological Museum, Insect Species Occurrence Data from Multiple Projects Worldwide with Focus on Bees and Wasps in North America, Bee Specimens from Michael Veit Collection, Cornell University Insect Collection (CUIC), Snow Entomological Museum Collection, Illinois Natural History Survey Insect Collection)",
 "TaxonKey is Melissodes apicatus"
 ]
}

 The dataset includes 192 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012271-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.85qcqy
title: Occurrence Download

description: A dataset containing 1473 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Menispermum dauricum",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 1473 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012274-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18484592
title: Artefatos do BodyCheck: Exploring the Use of Generative AI for Physical Assessment and Decision Support
DOI: 10.5281/zenodo.18486928
title: Artefatos do BodyCheck: Exploring the Use of Generative AI for Physical Assessment and Decision Support
DOI: 10.15468/dl.dz7uus
title: Occurrence Download

description: A dataset containing 15374 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aster bellidiastrum, Aster bellidiastrum, Aster bellidiastrum, Bellidiastrum michelii)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 15374 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012272-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25934/pr00012630.0
title: Available datapackage for study 'Supported Employment to Create a Community Culture of Rapid Testing Among People Who Inject Drugs: PeerConnect2Test'

description: Vivli is an independent, non-profit organization that has developed a global data-sharing and analytics platform to serve all elements of the international research community. Our mission is to promote, coordinate, and facilitate scientific sharing and reuse of clinical research data through the creation and implementation of a sustainable global data-sharing enterprise. The Vivli platform includes an independent data repository, in-depth search engine and a cloud-based, secure analytics platform.
DOI: 10.3886/e230862
title: Data and Code for: Substitution Bias and Fixed-Weight Price Indices in Time-Dependent Pricing Models

description: This paper compares measured inflation in true and fixed-weight price<br>indices. We construct model-based inflation measures in time-dependent<br>pricing models that are analogous to measures of inflation in the<br>data, e.g., the Consumer Price Index. In the standard new Keynesian<br>model, when inflation rises rapidly, the differences between inflation<br>in those indices and true price indices are increasing in the degree<br>of price stickiness and the elasticity of substitution across goods.<br>For commonly used parameter values, those differences are large and<br>persistent for increases in inflation of the size seen after 2020<br>in the U.S.
DOI: 10.3886/e230862v1
title: Data and Code for: Substitution Bias and Fixed-Weight Price Indices in Time-Dependent Pricing Models

description: This paper compares measured inflation in true and fixed-weight price<br>indices. We construct model-based inflation measures in time-dependent<br>pricing models that are analogous to measures of inflation in the<br>data, e.g., the Consumer Price Index. In the standard new Keynesian<br>model, when inflation rises rapidly, the differences between inflation<br>in those indices and true price indices are increasing in the degree<br>of price stickiness and the elasticity of substitution across goods.<br>For commonly used parameter values, those differences are large and<br>persistent for increases in inflation of the size seen after 2020<br>in the U.S.
DOI: 10.15468/dl.kw4b85
title: Occurrence Download

description: A dataset containing 42454 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "TaxonKey is Ricinus communis"
 ]
}

 The dataset includes 42454 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012275-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5519/qd.finqz6gm
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (2578256 records)
DOI: 10.15468/dl.f8bub7
title: Occurrence Download

description: A dataset containing 1843 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Astragalus cicer, Astragalus cicerellus, Astragalus cicerinus)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 1843 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012277-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5w47t9
title: Occurrence Download

description: A dataset containing 10057 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Leucaena leucocephala"
 ]
}

 The dataset includes 10057 records from 494 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012276-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18486900
title: Data and code supporting "How predictable was the May 2019 Arkansas River flooding? A case study."

description: Data and scripts used in the analysis described in "Western US Subseasonal Atmospheric River Prediction in the Global-Nested GFDL SHiELD Model."

Model output was created using the GFDL SHiELD model as described in Harris et al. (2020). SHiELD build and model physics codes can be found in the NOAA/GFDL GitHub repositories. A containerized version of SHiELD (Cheng et al., 2022) is also available at https://shield.gfdl.noaa.gov/shield-in-a-box/.

 

Cheng, K.-Y., Harris, L. M., and Sun, Y. Q. (2022). Enhancing the accessibility of unified modeling systems: GFDL System for High-resolution prediction on Earth-to-Local Domains (SHiELD) v2021b in a container. Geosci. Model Dev., 15, 1097-1105, https://doi.org/10.5194/gmd-15-1097-2022.

Harris, L. M., Zhou, L., Lin, S.-J., Chen, J.-H., Chen, X., Gao, K., et al. (2020). GFDL SHiELD: A unified system for weather-to-seasonal prediction. J. Adv. Model Earth Syst., 12(10), e2020MS002223, https://doi.org/10.1029/2020MS002223.
DOI: 10.5281/zenodo.18486899
title: Data and code supporting "How predictable was the May 2019 Arkansas River flooding? A case study."

description: Data and scripts used in the analysis described in "Western US Subseasonal Atmospheric River Prediction in the Global-Nested GFDL SHiELD Model."

Model output was created using the GFDL SHiELD model as described in Harris et al. (2020). SHiELD build and model physics codes can be found in the NOAA/GFDL GitHub repositories. A containerized version of SHiELD (Cheng et al., 2022) is also available at https://shield.gfdl.noaa.gov/shield-in-a-box/.

 

Cheng, K.-Y., Harris, L. M., and Sun, Y. Q. (2022). Enhancing the accessibility of unified modeling systems: GFDL System for High-resolution prediction on Earth-to-Local Domains (SHiELD) v2021b in a container. Geosci. Model Dev., 15, 1097-1105, https://doi.org/10.5194/gmd-15-1097-2022.

Harris, L. M., Zhou, L., Lin, S.-J., Chen, J.-H., Chen, X., Gao, K., et al. (2020). GFDL SHiELD: A unified system for weather-to-seasonal prediction. J. Adv. Model Earth Syst., 12(10), e2020MS002223, https://doi.org/10.1029/2020MS002223.
DOI: 10.15468/dl.4jyvvr
title: Occurrence Download

description: A dataset containing 242 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Odontocarya tamoides",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 242 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012278-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.my7y83
title: Occurrence Download

description: A dataset containing 271147 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "DatasetKey is EOD – eBird Observation Dataset",
 "GadmGid is USA.23_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Parulidae",
 "Year 2024-2024"
 ]
}

 The dataset includes 271147 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012245-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e228821
title: Data and Code for: Minority Salience and Criminal Justice Decisions

description: Decision-makers can exhibit biases when they overemphasize particularly salient features under limited attention. We exploit a sudden salience shock involving individuals of Moroccan descent to examine biases within the Dutch criminal justice system. The salience shock concerned the assassination of a defense attorney by organized crime and thus specifically targeted the justice system. Leveraging high-quality data covering arrest through appeal, we find no impact on police or prosecutor decisions but uncover a 71% increase in sentence lengths imposed by judges on salient individuals. Heterogeneity analyses suggest that judge experience with minority suspects can mitigate bias in these more discretionary decisions.
DOI: 10.3886/e228821v1
title: Data and Code for: Minority Salience and Criminal Justice Decisions

description: Decision-makers can exhibit biases when they overemphasize particularly salient features under limited attention. We exploit a sudden salience shock involving individuals of Moroccan descent to examine biases within the Dutch criminal justice system. The salience shock concerned the assassination of a defense attorney by organized crime and thus specifically targeted the justice system. Leveraging high-quality data covering arrest through appeal, we find no impact on police or prosecutor decisions but uncover a 71% increase in sentence lengths imposed by judges on salient individuals. Heterogeneity analyses suggest that judge experience with minority suspects can mitigate bias in these more discretionary decisions.