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

description: A dataset containing 550 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON((21.514594 39.776658,21.514594 39.713303,21.752641 39.713303,21.752641 39.776658,21.514594 39.776658))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 550 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009958-160311141623029/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.naegsw
title: Occurrence Download

description: A dataset containing 4726 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Biscutella auriculata L."
 ]
}

 The dataset includes 4726 records from 138 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053848-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ymprqg
title: Occurrence Download

description: A dataset containing 73 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lagothrix flavicauda (Humboldt, 1812)"
 ]
}

 The dataset includes 73 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069434-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0189784.10fu
title: SH0189784.10FU

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/sh0189785.10fu
title: SH0189785.10FU

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/sh0189786.10fu
title: SH0189786.10FU

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/sh0189787.10fu
title: SH0189787.10FU

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/sh0189788.10fu
title: SH0189788.10FU

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/sh0189789.10fu
title: SH0189789.10FU

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/sh0189790.10fu
title: SH0189790.10FU

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/sh0189791.10fu
title: SH0189791.10FU

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: 10.5522/04/28255484.v1
title: Priorities identified in the 2025 James Lind Alliance Palliative and End of Life Care Priority Setting Partnership, with supporting data and evidence

description: This data set details how data collected during the initial survey from the James Lind Alliance Palliative and End of Life Care Priority Setting Partnership was grouped into priorities for palliative and end of life care. It also includes references for existing systematic reviews that were identified, in relation to each of the priorities identified.
DOI: 10.5522/04/28255415.v1
title: Data from the initial survey of the 2025 James Lind Alliance Palliative and End of Life Care Priority Setting Partnership

description: Data set from initial survey from the 2025 James Lind Alliance Palliative and End of Life Care Priority Setting Partnership. This data was collected through on online survey which asked people living with a serious life limiting illness, their friends or family members, bereaved friends and family members and health and social care professionals involved in palliative and end of life care, the following question: "<i>Based on your experiences, what problems or needs should future research address to improve the experience of people with a serious, life-limiting illness and/or those close to them? " </i><i> </i>This research was funded by Marie Curie, The Motor Neuron Disease Association and the Economic and Social Research Council (ESRC) as part of UK Research and Innovation (UKRI).
DOI: 10.6084/m9.figshare.21995609.v1
title: Wetland water levels

description: Water level data file showing daily water levels in meter above sea level ffrom station in Rastmyran wetland, Uppland Sweden (Coordinates:  60.141270, 17.893285 )
DOI: 10.5522/04/28255415
title: Data from the initial survey of the 2025 James Lind Alliance Palliative and End of Life Care Priority Setting Partnership

description: Data set from initial survey from the 2025 James Lind Alliance Palliative and End of Life Care Priority Setting Partnership. This data was collected through on online survey which asked people living with a serious life limiting illness, their friends or family members, bereaved friends and family members and health and social care professionals involved in palliative and end of life care, the following question: "<i>Based on your experiences, what problems or needs should future research address to improve the experience of people with a serious, life-limiting illness and/or those close to them? " </i><i> </i>This research was funded by Marie Curie, The Motor Neuron Disease Association and the Economic and Social Research Council (ESRC) as part of UK Research and Innovation (UKRI).
DOI: 10.5522/04/28255484
title: Priorities identified in the 2025 James Lind Alliance Palliative and End of Life Care Priority Setting Partnership, with supporting data and evidence

description: This data set details how data collected during the initial survey from the James Lind Alliance Palliative and End of Life Care Priority Setting Partnership was grouped into priorities for palliative and end of life care. It also includes references for existing systematic reviews that were identified, in relation to each of the priorities identified.
DOI: 10.6084/m9.figshare.21995609
title: Wetland water levels

description: Water level data file showing daily water levels in meter above sea level ffrom station in Rastmyran wetland, Uppland Sweden (Coordinates:  60.141270, 17.893285 )
DOI: 10.15468/dl.tdfptk
title: Occurrence Download

description: A dataset containing 4747140 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Geometry POLYGON((-125.64 34.41,-108.26 34.41,-108.26 42.48,-125.64 42.48,-125.64 34.41))",
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 4747140 records from 467 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021841-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v3v6qc
title: Occurrence Download

description: A dataset containing 1964047 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((79.78294 10.26838, 79.81297 10.26928, 79.83843 10.27271, 79.86874 10.28107, 79.87498 10.28667, 87.04407 20.69961, 87.04405 20.70572, 86.99024 20.76405, 86.98291 20.76835, 86.9657 20.77465, 86.93134 20.77811, 86.8968 20.77744, 86.86323 20.77492, 86.82944 20.76325, 86.79558 20.74792, 86.76657 20.72883, 80.18822 15.78837, 80.17062 15.77334, 80.16006 15.75181, 80.15188 15.73074, 80.09186 15.47235, 79.39414 10.32927, 79.39359 10.31861, 79.73211 10.27332, 79.76096 10.26947, 79.78294 10.26838))"
 ]
}

 The dataset includes 1964047 records from 332 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021845-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ms25fb
title: Occurrence Download

description: A dataset containing 12056 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Stellaria pallida (Dumort.) Crép."
 ]
}

 The dataset includes 12056 records from 200 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021871-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gfvsc9
title: Occurrence Download

description: A dataset containing 5927 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "TaxonKey is Ips typographus (C.Linnaeus, 1758)",
 "Year 1990-2025"
 ]
}

 The dataset includes 5927 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021874-250127130748423/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.28218061
title: Ordered correlation forest

description: Empirical studies in various social sciences often involve categorical outcomes with inherent ordering, such as self-evaluations of subjective well-being and self-assessments in health domains. While ordered choice models, such as the ordered logit and ordered probit, are popular tools for analyzing these outcomes, they may impose restrictive parametric and distributional assumptions. This article introduces a novel estimator, the <i>ordered correlation forest,</i> that can naturally handle non linearities in the data and does not assume a specific error term distribution. The proposed estimator modifies a standard random forest splitting criterion to build a collection of forests, each estimating the conditional probability of a single class. Under an “honesty” condition, predictions are consistent and asymptotically normal. The weights induced by each forest are used to obtain standard errors for the predicted probabilities and the covariates’ marginal effects. Evidence from synthetic data shows that the proposed estimator features a superior prediction performance than alternative forest-based estimators and demonstrates its ability to construct valid confidence intervals for the covariates’ marginal effects. Comparisons using various real-world data sets further highlight the advantages of forest-based estimators over parametric models in larger samples while showing that the ordered correlation forest remains competitive in smaller samples.
DOI: 10.6084/m9.figshare.28218061.v1
title: Ordered correlation forest

description: Empirical studies in various social sciences often involve categorical outcomes with inherent ordering, such as self-evaluations of subjective well-being and self-assessments in health domains. While ordered choice models, such as the ordered logit and ordered probit, are popular tools for analyzing these outcomes, they may impose restrictive parametric and distributional assumptions. This article introduces a novel estimator, the <i>ordered correlation forest,</i> that can naturally handle non linearities in the data and does not assume a specific error term distribution. The proposed estimator modifies a standard random forest splitting criterion to build a collection of forests, each estimating the conditional probability of a single class. Under an “honesty” condition, predictions are consistent and asymptotically normal. The weights induced by each forest are used to obtain standard errors for the predicted probabilities and the covariates’ marginal effects. Evidence from synthetic data shows that the proposed estimator features a superior prediction performance than alternative forest-based estimators and demonstrates its ability to construct valid confidence intervals for the covariates’ marginal effects. Comparisons using various real-world data sets further highlight the advantages of forest-based estimators over parametric models in larger samples while showing that the ordered correlation forest remains competitive in smaller samples.
DOI: 10.15468/dl.7ywsns
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gastrolobium argyrotrichum Hislop, Wege & A.D.Webb"
 ]
}

 The dataset includes 9 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021876-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14841789
title: Impact of dialysate calcium concentration on intradialytic left ventricular function
DOI: 10.5281/zenodo.14841790
title: Impact of dialysate calcium concentration on intradialytic left ventricular function
DOI: 10.15468/dl.99ev8t
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Mongolia, Kazakhstan)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Aconitum septentrionale Koelle"
 ]
}

 The dataset includes 48 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021877-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9mcyeb
title: Occurrence Download

description: A dataset containing 120906 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Alces alces (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 120906 records from 140 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021865-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.942ytj
title: Occurrence Download

description: A dataset containing 2273632 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((79.00732 14.40573, 79.05717 14.4087, 79.23029 14.43209, 79.25571 14.43792, 79.27927 14.4488, 79.3401 14.48702, 81.1517 16.00505, 81.18377 16.07775, 81.37989 16.57977, 81.38902 16.60928, 81.41541 16.73542, 81.03855 20.89739, 81.03307 20.92747, 80.91789 21.40819, 80.90938 21.43912, 80.88766 21.46116, 80.80032 21.54469, 80.7737 21.5616, 79.47272 21.70338, 79.43742 21.70524, 79.36198 21.70515, 79.2926 21.702, 76.86197 21.21153, 75.94526 20.98318, 74.72048 20.61755, 74.6682 20.60119, 74.64403 20.58704, 74.62084 20.57106, 74.59566 20.5276, 74.52807 20.39215, 74.49752 20.31616, 74.48668 20.27313, 74.47731 20.20123, 74.47583 20.1733, 74.47778 20.1504, 74.48858 20.12748, 77.75011 15.04292, 77.88214 14.96698, 78.98382 14.40953, 79.00732 14.40573))"
 ]
}

 The dataset includes 2273632 records from 264 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021867-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3r6t87
title: Occurrence Download

description: A dataset containing 140184 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Avena fatua L."
 ]
}

 The dataset includes 140184 records from 1718 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021862-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.