cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.fsd9vu
title: Occurrence Download

description: A dataset containing 151734 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Peru",
 "Geometry POLYGON((-76.66249 -11.86272,-75.35101 -11.86272,-75.35101 -10.79112,-76.66249 -10.79112,-76.66249 -11.86272))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 151734 records from 312 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025627-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mpcbcj
title: Occurrence Download

description: A dataset containing 121 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Agave chiapensis Jacobi"
 ]
}

 The dataset includes 121 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025672-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/vjq3-c995
title: Round Lake diatom surface sample dataset

description: Raw data for the Round Lake diatom surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.yvknwj
title: Occurrence Download

description: A dataset containing 1401 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "DatasetKey is one of (Global Roadkill Data: a dataset on terrestrial vertebrate mortality caused by collision with vehicles (Systematic Records), Global Roadkill Data: a dataset on terrestrial vertebrate mortality caused by collision with vehicles (Opportunistic Records), Field Museum of Natural History (Zoology) Mammal Collection, NABU|naturgucker, Museu Paraense Emílio Goeldi - Mastozoology Collection, AMNH Mammal Collections, Brandt Meio Ambiente - Monitoramento da mastofauna terrestre - Usina Hidrelétrica de São Simão, Occurrences in SinBiota, NHMD Quaternary Zoology Collection)",
 "TaxonKey is Myrmecophaga tridactyla Linnaeus, 1758"
 ]
}

 The dataset includes 1401 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025677-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.my4cvd
title: Occurrence Download

description: A dataset containing 138 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "Geometry POLYGON((-78.53547 -5.64493,-78.54303 -5.63648,-78.55294 -5.64587,-78.54255 -5.65245,-78.53311 -5.6595,-78.46701 -5.72762,-78.44577 -5.74735,-78.43444 -5.7356,-78.44907 -5.73044,-78.45615 -5.72198,-78.46654 -5.7154,-78.47551 -5.70554,-78.48731 -5.69051,-78.48826 -5.68393,-78.49109 -5.67265,-78.52036 -5.64117,-78.53547 -5.64493))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 138 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025681-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/hhrx-fp30
title: Forez site 38 pollen surface sample dataset

description: Raw data for the Forez site 38 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.5281/zenodo.15297226
title: Molinia Heathlands: Field campaign 2022

description: A field campaign was conducted in August of  2022, when ground reference data were collected in four heathland areas across the Campine region (De Teut, Terhaagdoornheide, Averbode and De Maten). During this field campaign, per heathland area 40 plots were selected across the total range of Molinia caerulea coverage (%) present in the respective area. We made sure that each reference plot was located in relatively homogenous vegetation patch. The reference plots were circular with a radius of 5 meter. Within each plot, the coverage of M. caerulea was visually estimated in 10% bins. We refer to this dataset as the FC-2022 dataset, containing 160 plots.

This dataset is documented in the Data Management Plan for GEO.INFORMED use case 7 - Fire Hazard (DOI: 10.5281/zenodo.15350503)
DOI: 10.5281/zenodo.15297227
title: Molinia Heathlands: Field campaign 2022

description: A field campaign was conducted in August of  2022, when ground reference data were collected in four heathland areas across the Campine region (De Teut, Terhaagdoornheide, Averbode and De Maten). During this field campaign, per heathland area 40 plots were selected across the total range of Molinia caerulea coverage (%) present in the respective area. We made sure that each reference plot was located in relatively homogenous vegetation patch. The reference plots were circular with a radius of 5 meter. Within each plot, the coverage of M. caerulea was visually estimated in 10% bins. We refer to this dataset as the FC-2022 dataset, containing 160 plots.

This dataset is documented in the Data Management Plan for GEO.INFORMED use case 7 - Fire Hazard (DOI: 10.5281/zenodo.15350503)
DOI: 10.15468/dl.fkx85t
title: Occurrence Download

description: A dataset containing 1158 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "DatasetKey is one of (The Sustainable Wetlands Adaptation and Mitigation Program (SWAMP) Vegetation Dataset, HBRA - Herbário do Instituto de Estudos Costeiros da Universidade Federal do Pará, UEC - Herbário da Universidade Estadual de Campinas, ALCB herbarium - Universidade Federal da Bahia - Herbário Virtual REFLORA, RB - Rio de Janeiro Botanical Garden Herbarium Collection, NY herbarium - The New York Botanical Garden - Amostras Brasileiras Repatriadas - Herbário Virtual REFLORA, The New York Botanical Garden Herbarium (NY), ALCB - Herbário Alexandre Leal Costa, JPB - Herbário Lauro Pires Xavier)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Rhizophora mangle L."
 ]
}

 The dataset includes 1158 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025679-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/cv77-1966
title: LDDsite4867 water chemistry dataset

description: Raw data for the LDDsite4867 water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.mcf4jz
title: Occurrence Download

description: A dataset containing 472 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is French Guiana",
 "OccurrenceStatus is Present",
 "TaxonKey is Pieridae"
 ]
}

 The dataset includes 472 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025682-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/xx52-rd69
title: Stuphallet stream 4 pollen surface sample dataset

description: Raw data for the Stuphallet stream 4 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.hngnhy
title: Occurrence Download

description: A dataset containing 50434 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-80.74569 -3.81926,-80.14502 -3.81926,-80.14502 -3.34301,-80.74569 -3.34301,-80.74569 -3.81926))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 50434 records from 155 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025608-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4121/2e663686-f656-4ff2-bb21-567ba4d4f03e
title: Supplementary data for the paper: System 2 thinking in OpenAI’s o1-preview model: Near-perfect performance on a mathematics exam

description: The processes underlying human cognition are often divided into System 1, which involves fast, intuitive thinking, and System 2, which involves slow, deliberate reasoning. Previously, large language models were criticized for lacking the deeper, more analytical capabilities of System 2. In September 2024, OpenAI introduced the <em>o1</em> model series, designed to handle System 2-like reasoning. While OpenAI’s benchmarks are promising, independent validation is still needed. In this study, we tested the <em>o1-preview</em> model twice on the Dutch ‘Mathematics B’ final exam. It scored a near-perfect 76 and 74 out of 76 points. For context, only 24 out of 16,414 students in the Netherlands achieved a perfect score. By comparison, the <em>GPT-4o</em> model scored 66 and 62 out of 76, well above the Dutch average of 40.63 points. Neither model had access to the exam figures. Since there was a risk of model contamination (i.e., the knowledge cutoff of <em>o1-preview</em> and <em>GPT-4o</em> was after the exam was published online), we repeated the procedure with a new Mathematics B exam that was published after the cutoff date. The results again indicated that <em>o1-preview</em> performed strongly (97.8th percentile), which suggests that contamination was not a factor. We also show that there is some variability in the output of <em>o1-preview</em>, which means that sometimes there is ‘luck’ (the answer is correct) or ‘bad luck’ (the output has diverged into something that is incorrect). We demonstrate that a self-consistency approach, where repeated prompts are given and the most common answer is selected, is a useful strategy for identifying the correct answer. It is concluded that while OpenAI’s new model series holds great potential, certain risks must be considered.
DOI: 10.4121/2e663686-f656-4ff2-bb21-567ba4d4f03e.v1
title: Supplementary data for the paper 'System 2 thinking in OpenAI’s o1-preview model: Near-perfect performance on a mathematics exam'

description: The processes underlying human cognition are often divided into two systems: System 1, which involves fast, intuitive thinking, and System 2, which involves slow, deliberate reasoning. Previously, large language models were criticized for lacking the deeper, more analytical capabilities of System 2. In September 2024, OpenAI introduced the O1 model series, specifically designed to handle System 2-like reasoning. While OpenAI's benchmarks are promising, independent validation is still needed. In this study, we tested the O1-preview model twice on the Dutch ‘Mathematics B’ final exam. It scored a near-perfect 76 and 74 out of 76 points. For context, only 24 out of 16,414 students in the Netherlands achieved a perfect score. By comparison, the GPT-4o model scored 66 and 62 out of 76, well above the Dutch average of 40.63 points. The O1-preview model completed the exam in around 10 minutes, while GPT-4o took 3 minutes, and neither model had access to the exam figures. Although O1-preview had the ability to achieve a perfect score, its performance showed some variability, as it made occasional mistakes with repeated prompting. This suggests that the self-consistency method, where the consensus output is selected, could improve accuracy. We conclude that while OpenAI’s new model series holds great potential, certain risks must be considered.
DOI: 10.4121/2e663686-f656-4ff2-bb21-567ba4d4f03e.v2
title: Supplementary data for the paper 'System 2 thinking in OpenAI’s o1-preview model: Near-perfect performance on a mathematics exam'

description: The processes underlying human cognition are often divided into System 1, which involves fast, intuitive thinking, and System 2, which involves slow, deliberate reasoning. Previously, large language models were criticized for lacking the deeper, more analytical capabilities of System 2. In September 2024, OpenAI introduced the <em>o1</em> model series, designed to handle System 2-like reasoning. While OpenAI’s benchmarks are promising, independent validation is still needed. In this study, we tested the <em>o1-preview</em> model twice on the Dutch ‘Mathematics B’ final exam. It scored a near-perfect 76 and 74 out of 76 points. For context, only 24 out of 16,414 students in the Netherlands achieved a perfect score. By comparison, the <em>GPT-4o</em> model scored 66 and 62 out of 76, well above the Dutch average of 40.63 points. Neither model had access to the exam figures. Since there was a risk of model contamination (i.e., the knowledge cutoff of <em>o1-preview</em> and <em>GPT-4o</em> was after the exam was published online), we repeated the procedure with a new Mathematics B exam that was published after the cutoff date. The results again indicated that <em>o1-preview</em> performed strongly (97.8th percentile), which suggests that contamination was not a factor. We also show that there is some variability in the output of <em>o1-preview</em>, which means that sometimes there is ‘luck’ (the answer is correct) or ‘bad luck’ (the output has diverged into something that is incorrect). We demonstrate that a self-consistency approach, where repeated prompts are given and the most common answer is selected, is a useful strategy for identifying the correct answer. It is concluded that while OpenAI’s new model series holds great potential, certain risks must be considered.
DOI: 10.4121/2e663686-f656-4ff2-bb21-567ba4d4f03e.v3
title: Supplementary data for the paper: System 2 thinking in OpenAI’s o1-preview model: Near-perfect performance on a mathematics exam

description: The processes underlying human cognition are often divided into System 1, which involves fast, intuitive thinking, and System 2, which involves slow, deliberate reasoning. Previously, large language models were criticized for lacking the deeper, more analytical capabilities of System 2. In September 2024, OpenAI introduced the <em>o1</em> model series, designed to handle System 2-like reasoning. While OpenAI’s benchmarks are promising, independent validation is still needed. In this study, we tested the <em>o1-preview</em> model twice on the Dutch ‘Mathematics B’ final exam. It scored a near-perfect 76 and 74 out of 76 points. For context, only 24 out of 16,414 students in the Netherlands achieved a perfect score. By comparison, the <em>GPT-4o</em> model scored 66 and 62 out of 76, well above the Dutch average of 40.63 points. Neither model had access to the exam figures. Since there was a risk of model contamination (i.e., the knowledge cutoff of <em>o1-preview</em> and <em>GPT-4o</em> was after the exam was published online), we repeated the procedure with a new Mathematics B exam that was published after the cutoff date. The results again indicated that <em>o1-preview</em> performed strongly (97.8th percentile), which suggests that contamination was not a factor. We also show that there is some variability in the output of <em>o1-preview</em>, which means that sometimes there is ‘luck’ (the answer is correct) or ‘bad luck’ (the output has diverged into something that is incorrect). We demonstrate that a self-consistency approach, where repeated prompts are given and the most common answer is selected, is a useful strategy for identifying the correct answer. It is concluded that while OpenAI’s new model series holds great potential, certain risks must be considered.
DOI: 10.21233/xw4w-7014
title: La Chaux-des-Breuleux testate amoebae surface sample dataset

description: Raw data for the La Chaux-des-Breuleux testate amoebae surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.by9kev
title: Occurrence Download

description: A dataset containing 20929 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Country is Peru",
 "TaxonKey is Geonoma macrostachys Mart."
 ]
}

 The dataset includes 20929 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025686-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eqz7fs
title: Occurrence Download

description: A dataset containing 2432 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leopardus wiedii (Schinz, 1821)"
 ]
}

 The dataset includes 2432 records from 219 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025685-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/fpgh-ne15
title: Lundy L. ostracode surface sample dataset

description: Raw data for the Lundy L. ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/qkhy-0b90
title: Middle Pecos Valley Site P4 vertebrate fauna dataset

description: Raw data for the Middle Pecos Valley Site P4 vertebrate fauna dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/g9k1-se06
title: Wilson-Leonard [41WM235] vertebrate fauna dataset

description: Raw data for the Wilson-Leonard [41WM235] vertebrate fauna dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.zaee6u
title: Occurrence Download

description: A dataset containing 76 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is one of (Armenia, Georgia, Türkiye, Israel, Russian Federation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Capreolus capreolus (Linnaeus, 1758)",
 "Year 1990-2024"
 ]
}

 The dataset includes 76 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025690-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vzyeqp
title: Occurrence Download

description: A dataset containing 2432 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leopardus wiedii (Schinz, 1821)"
 ]
}

 The dataset includes 2432 records from 219 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025691-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/ky6f-g686
title: Kopparas Mire testate amoebae surface sample dataset

description: Raw data for the Kopparas Mire testate amoebae surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.tpatw7
title: Occurrence Download

description: A dataset containing 125838 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-76.01137 -10.35622,-75.1137 -10.35622,-75.1137 -9.70424,-76.01137 -9.70424,-76.01137 -10.35622))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 125838 records from 223 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025625-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/e6sf-5939
title: San Martin de Castaneda, charca al E. del Lago ostracode surface sample dataset

description: Raw data for the San Martin de Castaneda, charca al E. del Lago ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/jn7v-zh80
title: Apollo Beach vertebrate fauna dataset

description: Raw data for the Apollo Beach vertebrate fauna dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.xxgfja
title: Occurrence Download

description: A dataset containing 2266 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Cupressus funebris Endl."
 ]
}

 The dataset includes 2266 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025692-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/h864-dm73
title: Howling Dog South pollen surface sample dataset

description: Raw data for the Howling Dog South pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.