cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.uak9k8
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tephrosia purpurea",
 "Country is Burundi",
 "HasCoordinate is true"
 ]
}

 The dataset includes 38 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025436-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s6ruyj
title: Occurrence Download

description: A dataset containing 260 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tephrosia purpurea",
 "Country is Madagascar",
 "HasCoordinate is true"
 ]
}

 The dataset includes 260 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025437-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u74hz2
title: Occurrence Download

description: A dataset containing 49 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Iberus campesinus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 49 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025438-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jw4wze
title: Occurrence Download

description: A dataset containing 254 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Toona sinensis",
 "Geometry POLYGON((119.300000 20.500000, 122.100000 20.500000, 122.100000 25.400000, 119.300000 25.400000, 119.300000 20.500000))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 254 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025440-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p3zjaa
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tephrosia purpurea",
 "Country is Mauritius",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025443-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mt9edt
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tephrosia purpurea",
 "Country is Seychelles",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025444-250920141307145/datasets/export for details.
DOI: 10.15468/dl.fcyzbh
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Iberus carthaginiensis)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 9 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025441-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pq7h4j
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tephrosia purpurea",
 "Country is Malaysia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025442-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fh3nzh
title: Occurrence Download

description: A dataset containing 520 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Philippine Eagle Occurrence Records"
 ]
}

 The dataset includes 520 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025446-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cmy3vb
title: Occurrence Download

description: A dataset containing 1427 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cocculus orbiculatus",
 "Geometry POLYGON((119.300000 20.500000, 122.100000 20.500000, 122.100000 25.400000, 119.300000 25.400000, 119.300000 20.500000))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1427 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025448-250920141307145/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.30226309
title: Multimodal models play a critical role in mortality prediction for ICU patients.

description: Traditional emergency patient outcome models rely solely on structured data, overlooking critical insights from unstructured text (e.g., medical notes). We develop a multimodal framework integrating structured clinical metrics with natural language processing (NLP) of text data to predict ED outcomes. Compared to structured-only models, the multimodal approach improves the performance for mortality prediction, with NLP features enhancing interpretability. Combining structured and unstructured data captures holistic patient profiles, demonstrating that multimodal modeling boosts predictive accuracy in emergency care. These findings advocate for routine NLP integration in ED prediction systems.
DOI: 10.6084/m9.figshare.30226309.v1
title: Multimodal models play a critical role in mortality prediction for ICU patients.

description: Traditional emergency patient outcome models rely solely on structured data, overlooking critical insights from unstructured text (e.g., medical notes). We develop a multimodal framework integrating structured clinical metrics with natural language processing (NLP) of text data to predict ED outcomes. Compared to structured-only models, the multimodal approach improves the performance for mortality prediction, with NLP features enhancing interpretability. Combining structured and unstructured data captures holistic patient profiles, demonstrating that multimodal modeling boosts predictive accuracy in emergency care. These findings advocate for routine NLP integration in ED prediction systems.
DOI: 10.15468/dl.ewa67v
title: Occurrence Download

description: A dataset containing 69689 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oryza sativa",
 "Year 1975-2024"
 ]
}

 The dataset includes 69689 records from 337 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025363-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0186651.10fu
title: SH0186651.10FU

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/sh0186652.10fu
title: SH0186652.10FU

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/sh0186653.10fu
title: SH0186653.10FU

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/sh0186654.10fu
title: SH0186654.10FU

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/sh0186655.10fu
title: SH0186655.10FU

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/sh0186656.10fu
title: SH0186656.10FU

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/sh0186657.10fu
title: SH0186657.10FU

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/e242797
title: NHIS Interactive Biannual Early Release Estimates

description: Interactive Biannual Early Release Estimates provide health statistics based on data from the 2019-2021 National Health Interview Survey (NHIS) for selected health topics for adults aged 18 years and over. All estimates are unadjusted percentages based on preliminary data files and are released prior to final data editing and final weighting to provide access to the most recent information from the NHIS. Estimates can be grouped by demographic characteristics (such as age, race and Hispanic origin, or sex). Estimates based on 2019-2020 NHIS quarterly data are available in Interactive Quarterly Early Release Estimates. Estimates based on the 19972018 NHIS can be found in Previous Early Release Reports on Key Health Indicators.
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description: (Downloaded 1/7/2026)
DOI: 10.15156/bio/sh0186658.10fu
title: SH0186658.10FU

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/sh0186659.10fu
title: SH0186659.10FU

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/sh0186660.10fu
title: SH0186660.10FU

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/e242797v1
title: NHIS Interactive Biannual Early Release Estimates

description: Interactive Biannual Early Release Estimates provide health statistics based on data from the 2019-2021 National Health Interview Survey (NHIS) for selected health topics for adults aged 18 years and over. All estimates are unadjusted percentages based on preliminary data files and are released prior to final data editing and final weighting to provide access to the most recent information from the NHIS. Estimates can be grouped by demographic characteristics (such as age, race and Hispanic origin, or sex). Estimates based on 2019-2020 NHIS quarterly data are available in Interactive Quarterly Early Release Estimates. Estimates based on the 19972018 NHIS can be found in Previous Early Release Reports on Key Health Indicators.
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description: (Downloaded 1/7/2026)
DOI: 10.5281/zenodo.18134076
title: Middle Orthomosaic for Bywater-Reyes et al. (2026) Resilient St Vrain Assessment

description: Dataset associated with Bywater-Reyes et al., 2026, Lessons Learned from a Post Flood-Reconstruction Project of an Urban Stream (Resilient St. Vrain, Longmont, Colorado, USA), Geomorphology

Orthomosaic for the middle section of the study area.

The study region was captured with drone imagery and overlapping images were post-processed for orthorectified aerial imagery and Structure from Motion (SfM) topography following best practices (Brodu & Lague, 2012; Westoby et al., 2012) using Agisoft Metashape. Additional in-channel topography and ground control were surveyed with RTK GPS. For SfM, ground control points (GCPs) were collected using a Trimble R10 unit with real-time corrections using their RTX service (EPSG:32613 coordinate system; WGS 84 / UTM zone 13N). Control point accuracy was within 1 cm horizontally and 5 cm vertically. Targets were a mix of black and white squares, 24in x 24in, as well as “X”’s created using strips of orange hazard tape. The aerial survey was performed on July 22, 2022 using a Matrice 100 UAV with a Rededge-M legacy 5-band sensor at 90 meters flight height with >80% overlap in imagery in both directions. Imagery was postprocessed with GCPs following the protocol outlined in (Bywater-Reyes & Pratt-Sitaula, 2022). Products included digital elevation models (DEMs) and multispectral orthomosaics.
DOI: 10.5281/zenodo.18134077
title: Middle Orthomosaic for Bywater-Reyes et al. (2026) Resilient St Vrain Assessment

description: Dataset associated with Bywater-Reyes et al., 2026, Lessons Learned from a Post Flood-Reconstruction Project of an Urban Stream (Resilient St. Vrain, Longmont, Colorado, USA), Geomorphology

Orthomosaic for the middle section of the study area.

The study region was captured with drone imagery and overlapping images were post-processed for orthorectified aerial imagery and Structure from Motion (SfM) topography following best practices (Brodu & Lague, 2012; Westoby et al., 2012) using Agisoft Metashape. Additional in-channel topography and ground control were surveyed with RTK GPS. For SfM, ground control points (GCPs) were collected using a Trimble R10 unit with real-time corrections using their RTX service (EPSG:32613 coordinate system; WGS 84 / UTM zone 13N). Control point accuracy was within 1 cm horizontally and 5 cm vertically. Targets were a mix of black and white squares, 24in x 24in, as well as “X”’s created using strips of orange hazard tape. The aerial survey was performed on July 22, 2022 using a Matrice 100 UAV with a Rededge-M legacy 5-band sensor at 90 meters flight height with >80% overlap in imagery in both directions. Imagery was postprocessed with GCPs following the protocol outlined in (Bywater-Reyes & Pratt-Sitaula, 2022). Products included digital elevation models (DEMs) and multispectral orthomosaics.