cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ekg69v
title: Occurrence Download

description: A dataset containing 328 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-98.53103 29.44924,-98.53098 29.44886,-98.53066 29.44884,-98.53029 29.44873,-98.52967 29.44843,-98.52899 29.44833,-98.52873 29.44807,-98.52849 29.4465,-98.5285 29.44414,-98.52874 29.44265,-98.52855 29.44169,-98.52756 29.4407,-98.5274 29.43862,-98.5276 29.43856,-98.52774 29.43802,-98.52748 29.43791,-98.52743 29.43768,-98.5267 29.43743,-98.52575 29.43735,-98.52443 29.43681,-98.523 29.43593,-98.52229 29.43519,-98.52219 29.43479,-98.52175 29.43434,-98.52048 29.43413,-98.51927 29.43396,-98.51873 29.43368,-98.51846 29.43335,-98.51836 29.43222,-98.51742 29.43173,-98.51631 29.43124,-98.51581 29.43051,-98.51459 29.43035,-98.51375 29.43007,-98.51353 29.42969,-98.51373 29.42806,-98.51359 29.42696,-98.51337 29.42653,-98.51297 29.42511,-98.51145 29.42409,-98.51051 29.42324,-98.50955 29.42163,-98.50981 29.41981,-98.51002 29.41714,-98.5099 29.41697,-98.50991 29.41612,-98.5094 29.41561,-98.50873 29.41517,-98.50836 29.41468,-98.50844 29.41434,-98.50912 29.41243,-98.50889 29.41181,-98.50848 29.41252,-98.50774 29.41428,-98.50812 29.41537,-98.5092 29.41619,-98.50894 29.42174,-98.51037 29.4241,-98.51216 29.42506,-98.51308 29.42702,-98.51296 29.42822,-98.51301 29.42989,-98.51371 29.43071,-98.51536 29.43089,-98.51597 29.43154,-98.51763 29.43234,-98.51765 29.43309,-98.51792 29.43345,-98.51826 29.43397,-98.51966 29.43434,-98.52155 29.43477,-98.52213 29.43556,-98.52318 29.43658,-98.52475 29.43747,-98.52667 29.43814,-98.52689 29.43892,-98.52709 29.44005,-98.52732 29.44078,-98.52754 29.44101,-98.52817 29.44167,-98.52838 29.44203,-98.52848 29.44247,-98.52839 29.44268,-98.52808 29.4439,-98.52799 29.44481,-98.52802 29.4459,-98.52808 29.44658,-98.52814 29.44696,-98.5281 29.44823,-98.52842 29.44827,-98.52846 29.44881,-98.52815 29.44881,-98.52797 29.44983,-98.5302 29.44939,-98.53103 29.44924))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 328 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050003-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23641/asha.25511191
title: Intervention intensity in mobile health (Cordella & Kiran, 2024)

description: <b>Purpose: </b>Cumulative Intervention Intensity (CII) is a proposed framework for conceptualizing and calculating dose that has been used to quantify intensity of speech-language therapy (SLT) in highly controlled laboratory studies and clinical trials. However, it is unknown whether CII can be applied to characterize the practice patterns of patients undertaking at-home, self-managed SLT. The current study leverages real-world mobile health data to investigate the applicability of CII parameters to self-managed SLT, including the interrelationships between individual CII parameters and their utility for identifying naturally occurring subgroups of patient users.<b>Method:</b> Anonymized data from 2,223 poststroke survivors who used the Constant Therapy application were analyzed. Four quantitative CII parameters—dose, session frequency, session duration, and total intervention duration—were calculated per user over a 3-month analysis period using raw session-level data. We conducted correlation analyses at the level of the individual and group to examine the degree of relatedness between each of the CII parameters. CII parameter measures were additionally used as inputs to a k-mean clustering analysis to identify practice pattern subgroups.<b>Results:</b> Results demonstrate the feasibility of calculating components of CII based on available usage statistics from a commercial app for self-managed SLT. Specifically, results suggest that, although CII parameters are related, session frequency offers complementary and nonoverlapping information (cf. dose, session duration, total intervention duration) about dosage. Clustering results show that practice patterns can be broadly differentiated according to the (a) amount and (b) frequency of practice.<b>Conclusions:</b> The calculation of CII may provide both users and clinicians with a fuller picture of at-home, self-managed practice habits than looking at any one dosage component alone. The study represents a first step toward more comprehensive and theoretically grounded dose reporting for self-managed SLT.<b>Supplemental Material S1</b>. CII and component quantitative parameters by individual task domain.Cordella, C., & Kiran, S. (2024). Quantifying dosage in self-managed speech-language therapy: Exploring components of Cumulative Intervention Intensity in a real-world mobile health data set. <i>American Journal of Speech-Language Pathology</i>, <i>33</i>(3), 1513–1523. https://doi.org/10.1044/2024_AJSLP-23-00285
DOI: 10.23641/asha.25511191.v1
title: Intervention intensity in mobile health (Cordella & Kiran, 2024)

description: <b>Purpose: </b>Cumulative Intervention Intensity (CII) is a proposed framework for conceptualizing and calculating dose that has been used to quantify intensity of speech-language therapy (SLT) in highly controlled laboratory studies and clinical trials. However, it is unknown whether CII can be applied to characterize the practice patterns of patients undertaking at-home, self-managed SLT. The current study leverages real-world mobile health data to investigate the applicability of CII parameters to self-managed SLT, including the interrelationships between individual CII parameters and their utility for identifying naturally occurring subgroups of patient users.<b>Method:</b> Anonymized data from 2,223 poststroke survivors who used the Constant Therapy application were analyzed. Four quantitative CII parameters—dose, session frequency, session duration, and total intervention duration—were calculated per user over a 3-month analysis period using raw session-level data. We conducted correlation analyses at the level of the individual and group to examine the degree of relatedness between each of the CII parameters. CII parameter measures were additionally used as inputs to a k-mean clustering analysis to identify practice pattern subgroups.<b>Results:</b> Results demonstrate the feasibility of calculating components of CII based on available usage statistics from a commercial app for self-managed SLT. Specifically, results suggest that, although CII parameters are related, session frequency offers complementary and nonoverlapping information (cf. dose, session duration, total intervention duration) about dosage. Clustering results show that practice patterns can be broadly differentiated according to the (a) amount and (b) frequency of practice.<b>Conclusions:</b> The calculation of CII may provide both users and clinicians with a fuller picture of at-home, self-managed practice habits than looking at any one dosage component alone. The study represents a first step toward more comprehensive and theoretically grounded dose reporting for self-managed SLT.<b>Supplemental Material S1</b>. CII and component quantitative parameters by individual task domain.Cordella, C., & Kiran, S. (2024). Quantifying dosage in self-managed speech-language therapy: Exploring components of Cumulative Intervention Intensity in a real-world mobile health data set. <i>American Journal of Speech-Language Pathology</i>, <i>33</i>(3), 1513–1523. https://doi.org/10.1044/2024_AJSLP-23-00285
DOI: 10.15468/dl.jcxx64
title: Occurrence Download

description: A dataset containing 76223 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Equatorial Guinea"
 ]
}

 The dataset includes 76223 records from 231 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003319-151016162008034/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9dewew
title: Occurrence Download

description: A dataset containing 730 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Rhododendron arboreum Sm."
 ]
}

 The dataset includes 730 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053078-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8aieeu
title: Occurrence Download

description: A dataset containing 94 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anthophora coptognatha Timberlake, 1951",
 "HasCoordinate is true"
 ]
}

 The dataset includes 94 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003319-160526112335914/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vetnap
title: Occurrence Download

description: A dataset containing 3355 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coryphaenoides rupestris Gunnerus, 1765"
 ]
}

 The dataset includes 3355 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049989-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wgeg4o
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vipera berus (Linnaeus, 1758)",
 "Country is Belgium"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003319-160822134323880/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ys572m
title: Occurrence Download

description: A dataset containing 30220 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ctenolabrus rupestris (Linnaeus, 1758)"
 ]
}

 The dataset includes 30220 records from 150 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050009-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ijv8tn
title: Occurrence Download

description: A dataset containing 47 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eryx jaculus (Daudin, 1803)"
 ]
}

 The dataset includes 47 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003319-170925132151566/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aaptve
title: Occurrence Download

description: A dataset containing 111 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Parabuthus laevifrons (Simon, 1888)"
 ]
}

 The dataset includes 111 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054758-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.lietzw
title: Occurrence Download

description: A dataset containing 163 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Aegilops bicornis (Forssk.) Jaub. & Spach",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 163 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003319-171002173027117/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dat4hn
title: Occurrence Download

description: A dataset containing 135 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Vasconcellea A.St.-Hil."
 ]
}

 The dataset includes 135 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054092-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dvldjr
title: Occurrence Download

description: A dataset containing 502 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Trianthema portulacastrum L."
 ]
}

 The dataset includes 502 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003319-171124123535762/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mq4ath
title: Occurrence Download

description: A dataset containing 602 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chamaeleonidae",
 "Continent is one of (North America, South America)"
 ]
}

 The dataset includes 602 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054087-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4k35t8
title: Occurrence Download

description: A dataset containing 1673 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Liriodendron tulipifera L.",
 "BasisOfRecord is one of (Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (United States of America, Canada)"
 ]
}

 The dataset includes 1673 records from 92 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0270810-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2wagh4
title: Occurrence Download

description: A dataset containing 2230111 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 "Country is Ukraine"
 ]
}

 The dataset includes 2230111 records from 767 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054091-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0196306.10fu
title: SH0196306.10FU

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/sh0196307.10fu
title: SH0196307.10FU

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/sh0196308.10fu
title: SH0196308.10FU

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/sh0196309.10fu
title: SH0196309.10FU

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/sh0196310.10fu
title: SH0196310.10FU

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/sh0196311.10fu
title: SH0196311.10FU

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/sh0196312.10fu
title: SH0196312.10FU

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/sh0196313.10fu
title: SH0196313.10FU

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.