cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/yeaj85
title: Replication Data for: How Language Shapes Belief in Misinformation: A Study Among Multilinguals in Ukraine

description: Scholarship has identified key determinants of people's belief in misinformation, predominantly from English-language contexts. However, multilingual citizens often consume news media in multiple languages. We study how language of consumption affects belief in misinformation and true news articles in multilingual environments. We suggest that language may pass on specific cues affecting how bilinguals evaluate information. In a ten-week survey experiment with bilingual adults in Ukraine, we measure if subjects evaluating information in their less-preferred language were less likely to believe it. We find those who prefer Ukrainian are less likely to believe both false and true stories written in Russian by approximately .2 standard deviation units. Conversely, those who prefer Russian show increased belief in false stories in Ukrainian, though this effect is less robust. A secondary digital media literacy intervention does not increase discernment as it reduces belief in both true and false stories equally.
DOI: 10.15468/dl.8tf9qa
title: Occurrence Download

description: A dataset containing 52672 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is one of (Saint Vincent and the Grenadines, Grenada)"
 ]
}

 The dataset includes 52672 records from 423 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069130-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ut68tg
title: Occurrence Download

description: A dataset containing 1312 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leopardus tigrinus (Schreber, 1775)"
 ]
}

 The dataset includes 1312 records from 142 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069132-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7c4xss
title: Occurrence Download

description: A dataset containing 655755 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-450.13389 48.05139,-447.54302 48.05139,-447.54302 50.29349,-450.13389 50.29349,-450.13389 48.05139))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 655755 records from 373 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069127-250525065834625/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.29120657
title: Figure 7 and Tables 5-14

description: Supplemental Figure 7 and Supplemental Tables 5-14
DOI: 10.6084/m9.figshare.29120657.v1
title: Figure 7 and Tables 5-14

description: Supplemental Figure 7 and Supplemental Tables 5-14
DOI: 10.60503/d3/5uievi
title: AIDA Ukrainian Broadcast and Telephone Speech Audio and Transcripts

description: AIDA Ukrainian Broadcast and Telephone Speech Audio and Transcripts was developed by the Linguistic Data Consortium (LDC) and is comprised of approximately 156 hours of Ukrainian conversational telephone speech (CTS) and broadcast news audio (BN) with 1.2 million words of corresponding orthographic transcripts. The broadcast recordings and transcripts were produced to support the DARPA AIDA (Active Interpretation of Disparate Alternatives) program which aimed to develop a multi-hypothesis semantic engine to generate explicit alternative interpretations of events, situations and trends from a variety of unstructured sources. LDC supported AIDA by collecting, creating and annotating multimodal linguistic resources in multiple languages. The telephone speech audio recordings were collected to support the NIST 2011 Language Recognition Evaluation which focused on pair discrimination for 24 languages/dialects. These recording are also contained in Multi-Language Conversational Telephone Speech 2011 – Slavic Group LDC2016S11. The goal of NIST’s LRE series is to establish the baseline of current performance capability for language recognition of conversational telephone speech and to lay the groundwork for further research efforts in the field.
DOI: 10.15468/dl.499q3u
title: Occurrence Download

description: A dataset containing 38647 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 "TaxonKey is one of (Buteo platypterus (Vieillot, 1823))"
 ]
}

 The dataset includes 38647 records from 158 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069135-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15741970
title: Dataset: two model impedances + associated complex-valued distribution of uncorrelated relaxation times

description: Z1_EEC.png electric circuit model #1Z1_data.dat impedance data for electric circuit model #1DRT_Z1_data.dat DRT data for electric circuit model #1Z2_EEC.png electric circuit model #2Z2_data.dat impedance data for electric circuit model #2DRT_Z2_data.dat DRT data for electric circuit model #2

Z2_data_corrected.dat corrected impedance data for electric circuit model #2 to replace Z2_data.dat

Nyquist_Z2_model_corrected.png Nyquist plot electric circuit model #2 to replace Figure 4 (bottom left) in https://doi.org/10.1016/j.electacta.2025.146500

Bode_Z2_model_corrected.png Bode plot electric circuit model #2 to replace Figure 4 (bottom right) in https://doi.org/10.1016/j.electacta.2025.146500
DOI: 10.15468/dl.fjm6g6
title: Occurrence Download

description: A dataset containing 52672 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is one of (Saint Vincent and the Grenadines, Grenada)"
 ]
}

 The dataset includes 52672 records from 423 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069133-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15741935
title: Material suplementario 1. Desarrollo de la competencia argumentativa en estudiantes de enfermería a través del razonamiento clínico sobre bacterias: Un estudio de caso

description: Este conjunto de datos incluye materiales y resultados asociados a un estudio mixto, con predominio cualitativo, sobre el desarrollo de la competencia argumentativa en estudiantes de enfermería mediante el razonamiento clínico contextualizado en el aprendizaje sobre bacterias. La intervención se llevó a cabo con 40 estudiantes de segundo semestre del programa de Enfermería de la Unidad Central del Valle del Cauca (UCEVA), Colombia, e integró el modelo de argumentación de Toulmin para promover razonamientos clínicos basados en evidencia.

 

El material contiene:



CUADRO_DE_ANALISIS_DE_LOS_4_MOMENTOS.xlsx : Desglose pedagógico del progreso de los estudiantes en cuatro momentos evaluativos, mostrando transiciones entre niveles de competencia argumentativa (Bajo, Medio, Alto).

Material suplementario 1.docx : Interpretación pedagógica de las transiciones en el desarrollo de habilidades cognitivas, junto con implicaciones didácticas para el acompañamiento diferenciado.

Tabulacion de los 4 momentos de intervención.xlsx : Registro de respuestas estudiantiles a cuestionarios de casos clínicos, utilizados para evaluar el avance en la competencia argumentativa y el razonamiento clínico durante la unidad didáctica.


 

Estos datos respaldan el análisis longitudinal del impacto de una estrategia educativa innovadora en la formación en salud, destacando mejoras significativas en la precisión de datos, justificaciones y confianza estudiantil al aplicar conocimientos microbiológicos en contextos clínicos.
DOI: 10.15468/dl.jv4sbb
title: Occurrence Download

description: A dataset containing 474 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ficus albert-smithii Standl."
 ]
}

 The dataset includes 474 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069137-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15522209
title: State Space-Based Methods for Validating Model Transformations in Model Checkers (Dataset)

description: Artifact

These directories contain all necessary files and our results for our evaluation, and additionally, to our motivation example for the paper titled "State Space-Based Methods for Validating Model Transformations in Model Checkers" by Zsófia Ádám and Zoltán Micskei.

These files are available directly in the zenodo archive, but the provided Ubuntu VM also contains a copy of this directory.

DOI of the paper: TBA

About the Virtual Machine

VM username and password: artifact

The VM is a simple ubuntu 24.04.1 Desktop install with the following additional packages (and their dependencies) installed from apt:openssh-servergraphvizdotopenjdk-17-jre-headless

It has 8GB of RAM, a 35GB disk and 12 CPU cores.

It is a kvm VM, thus a qcow2 disk and the exported XML of the VM is provided. Change the <file> path to the qcow2 file before importing it.

Data Folders

These are available separately and on the virtual machine as well.

Motivation Example

This is the motivation example of HugoRT battery models from the beginning of the paper.

Evaluation

This is our main evaluation executed on the Gamma-Theta toolchain from the last section of the paper.

Textual source (gcd extension) and PlantUML visualisations for each model are also provided, eliminating the need to run Gamma and the Eclipse IDE for just checking the model suite.

Both the evaluation and the motivation example include their own readmes.
DOI: 10.5281/zenodo.15741889
title: State Space-Based Methods for Validating Model Transformations in Model Checkers (Dataset)

description: Artifact

These directories contain all necessary files and our results for our evaluation, and additionally, to our motivation example for the paper titled "State Space-Based Methods for Validating Model Transformations in Model Checkers" by Zsófia Ádám and Zoltán Micskei.

These files are available directly in the zenodo archive, but the provided Ubuntu VM also contains a copy of this directory.

DOI of the paper: TBA

About the Virtual Machine

VM username and password: artifact

The VM is a simple ubuntu 24.04.1 Desktop install with the following additional packages (and their dependencies) installed from apt:openssh-servergraphvizdotopenjdk-17-jre-headless

It has 8GB of RAM, a 35GB disk and 12 CPU cores.

It is a kvm VM, thus a qcow2 disk and the exported XML of the VM is provided. Change the <file> path to the qcow2 file before importing it.

Data Folders

These are available separately and on the virtual machine as well.

Motivation Example

This is the motivation example of HugoRT battery models from the beginning of the paper.

Evaluation

This is our main evaluation executed on the Gamma-Theta toolchain from the last section of the paper.

Textual source (gcd extension) and PlantUML visualisations for each model are also provided, eliminating the need to run Gamma and the Eclipse IDE for just checking the model suite.

Both the evaluation and the motivation example include their own readmes.
DOI: 10.5281/zenodo.15741662
title: Nitrate levels in irrigation water across the Wisconsin Central Sands

description: This dataset containes measuremetns of nitrate levels in irrigation water across the Central Sands region of Wisconsin. Data was collected during the 2018, 2019, and 2020 growing seasons. Related information on well consturction and nitrogen application rates are also included and were used in further analysis. The dataset was used in the following peer-reviewed publication: Campbell, T. A., Masarik, K. C., Heineman, E. M., & Kucharik, C. J. (2023). Quantifying the spatiotemporal variability of nitrate in irrigation water across the Wisconsin Central Sands (Vol. 52, No. 6, pp. 1102-1114). https://doi.org/10.1002/jeq2.20521
DOI: 10.5281/zenodo.15741663
title: Nitrate levels in irrigation water across the Wisconsin Central Sands

description: This dataset containes measuremetns of nitrate levels in irrigation water across the Central Sands region of Wisconsin. Data was collected during the 2018, 2019, and 2020 growing seasons. Related information on well consturction and nitrogen application rates are also included and were used in further analysis. The dataset was used in the following peer-reviewed publication: Campbell, T. A., Masarik, K. C., Heineman, E. M., & Kucharik, C. J. (2023). Quantifying the spatiotemporal variability of nitrate in irrigation water across the Wisconsin Central Sands (Vol. 52, No. 6, pp. 1102-1114). https://doi.org/10.1002/jeq2.20521
DOI: 10.15468/dl.zxvq9r
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Geometry POLYGON((-125.05372 42.25248,-113.59139 42.25248,-113.59139 49.51543,-125.05372 49.51543,-125.05372 42.25248))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Habropoda depressa Fowler, 1899"
 ]
}

 The dataset includes 13 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069139-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hfwsmp
title: Occurrence Download

description: A dataset listing the 47180 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Continent is North America",
 "Geometry POLYGON((-84.03371 49.66888,-91.20857 49.51305,-94.95999 46.48106,-92.75805 40.61174,-89.26383 37.95874,-81.29566 37.29102,-76.80893 39.5554,-75.31498 44.07309,-76.35848 47.57068,-84.03371 49.66888))",
 "HasGeospatialIssue is false",
 "TaxonKey is Animalia"
 ]
}

 The dataset's 47180 records were derived from 678 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069138-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0185759.10fu
title: SH0185759.10FU

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/sh0185760.10fu
title: SH0185760.10FU

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/sh0185761.10fu
title: SH0185761.10FU

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/sh0185762.10fu
title: SH0185762.10FU

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/sh0185763.10fu
title: SH0185763.10FU

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/sh0185764.10fu
title: SH0185764.10FU

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/sh0185765.10fu
title: SH0185765.10FU

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/sh0185766.10fu
title: SH0185766.10FU

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.