cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17144271
title: EmiliaCap-5k

description: Description

The EmiliaCap-5k dataset provides emotion, pitch, energy, and caption annotations for 2,158,308 audio files from the Emilia-YODAS dataset, corresponding to approximately 5,898 hours of speech.

Annotations were generated using a fine-tuned Qwen2-Audio captioning model that leverages chain-of-thought reasoning and a curriculum-learning training schedule. The model was designed to first predict intermediate attributes (emotion, pitch, and energy) before producing the final natural-language caption.

The model was trained on roughly 40,000 samples from the TextrolSpeech dataset and demonstrated superior performance compared to 500 alternative configurations, measured using a task-specific caption similarity metric.

 

Contents

The dataset consists of a single TSV file with the following fields:



 path: File identifier following the Emilia-YODAS filename convention

 emotion: Emotion label (`happy`, `neutral`, `sad`, `angry`, `disgusted`, `surprised`, `contempt`, `fear`)

 pitch: Pitch label (`low`, `normal`, `high`)

 energy: Energy label (`low`, `normal`, `high`)

 caption: Natural-language caption


---

Intended Use

The EmiliaCap-5k dataset is primarily intended as training and evaluation data for controllable text-to-speech (TTS) systems, where conditioning on emotion, pitch, and energy is required.

Other potential use cases include:

* Benchmarking audio captioning models that predict fine-grained paralinguistic features* Studying the interaction between emotion, pitch, energy, and natural-language descriptions* Enabling multimodal research that connects speech signals with structured annotations and captions

---

Limitations



The annotations were automatically generated by a machine learning model and may contain noise or systematic biases.

Emotion, pitch, and energy are categorical labels, which may not capture the full nuance of continuous variation.

Captions are optimized for similarity-based metrics rather than human readability, and may therefore differ from human-style captions.


---

Citation

If you use this dataset, please cite it as:

TBA
DOI: 10.5281/zenodo.17144270
title: EmiliaCap-5k

description: Description

The EmiliaCap-5k dataset provides emotion, pitch, energy, and caption annotations for 2,158,308 audio files from the Emilia-YODAS dataset, corresponding to approximately 5,898 hours of speech.

Annotations were generated using a fine-tuned Qwen2-Audio captioning model that leverages chain-of-thought reasoning and a curriculum-learning training schedule. The model was designed to first predict intermediate attributes (emotion, pitch, and energy) before producing the final natural-language caption.

The model was trained on roughly 40,000 samples from the TextrolSpeech dataset and demonstrated superior performance compared to 500 alternative configurations, measured using a task-specific caption similarity metric.

 

Contents

The dataset consists of a single TSV file with the following fields:



 path: File identifier following the Emilia-YODAS filename convention

 emotion: Emotion label (`happy`, `neutral`, `sad`, `angry`, `disgusted`, `surprised`, `contempt`, `fear`)

 pitch: Pitch label (`low`, `normal`, `high`)

 energy: Energy label (`low`, `normal`, `high`)

 caption: Natural-language caption


---

Intended Use

The EmiliaCap-5k dataset is primarily intended as training and evaluation data for controllable text-to-speech (TTS) systems, where conditioning on emotion, pitch, and energy is required.

Other potential use cases include:

* Benchmarking audio captioning models that predict fine-grained paralinguistic features* Studying the interaction between emotion, pitch, energy, and natural-language descriptions* Enabling multimodal research that connects speech signals with structured annotations and captions

---

Limitations



The annotations were automatically generated by a machine learning model and may contain noise or systematic biases.

Emotion, pitch, and energy are categorical labels, which may not capture the full nuance of continuous variation.

Captions are optimized for similarity-based metrics rather than human readability, and may therefore differ from human-style captions.


---

Citation

If you use this dataset, please cite it as:

TBA
DOI: 10.18141/2587096
title: CT and Geophysical Data of Clinton Sandstone Cores from Ohio

description: Collection of computed tomography and multi-sensor core logger data of 12 wells in Ohio that intersect the Clinton Sandstone formation. This data is described along with well information in a technical report series document:
Paronish, T.; Holleran, A.; Pohl, M.; Crandall, D.; Jarvis, K.; Workman, S.; Drosche, J.; McKisic, T.; Collins, C.; Thomas, M.; McDonald, J. Computed Tomography Scanning and Geophysical Measurements of the Clinton Sandstone in Ohio; DOE.NETL-2025.4949; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory, Morgantown, WV, 2025; p 68. https://doi.org/10.2172/2589262
DOI: 10.13140/rg.2.2.20840.53761
title: To Ajarn Sanu Development of Critical Thinking Skills Through Project
DOI: 10.7910/dvn/lzlqep
title: Paired Simulation Scenario Ratings for AI vs Human Authors

description: 5 expert raters used the SSET tool to evaluate 5 paired (AI vs Human created) scenarios, reported perceived authorship, and rated suitability for deployment
DOI: 10.15468/dl.wgce4k
title: Occurrence Download

description: A dataset containing 7142 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Galanthus elwesii"
 ]
}

 The dataset includes 7142 records from 122 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015619-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p8heh6
title: Occurrence Download

description: A dataset containing 40 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "PublishingOrg is one of (8483a1f0-1032-11db-ae00-b8a03c50a862, bc092ff0-02e4-11dc-991f-b8a03c50a862, f9b67ad0-9c9b-11d9-b9db-b8a03c50a862, b4640710-8e03-11d8-b956-b8a03c50a862, cc6110c7-f75c-47c8-8931-f7dd3f324777, 6ea87510-0561-11d8-b851-b8a03c50a862, 66522820-055c-11d8-b84e-b8a03c50a862, 021121c0-f040-11d8-b22f-b8a03c50a862, ff90b050-c256-11db-b71b-b8a03c50a862)",
 "TaxonKey is Tarebia granifera (Lamarck, 1816)"
 ]
}

 The dataset includes 40 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058734-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.abwvpu
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((149.894399 -33.550523, 149.898891 -33.550523, 149.898891 -33.548277, 149.894399 -33.548277, 149.894399 -33.550523)), ((149.894399 -33.550523, 149.892154 -33.550523, 149.892154 -33.555015, 149.894399 -33.555015, 149.894399 -33.550523)))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058735-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yjqmcp
title: Occurrence Download

description: A dataset containing 1003 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Penelope jacucaca Spix, 1825"
 ]
}

 The dataset includes 1003 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058736-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9586yq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.789466 -33.550523, 148.789466 -33.555015, 148.796204 -33.555015, 148.796204 -33.550523, 148.789466 -33.550523))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058737-240626123714530/datasets/export for details.
DOI: 10.15468/dl.dswe5w
title: Occurrence Download

description: A dataset containing 524 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is one of (Canada, United States of America)",
 "TaxonKey is Hylesinus varius (J.C.Fabricius, 1775)"
 ]
}

 The dataset includes 524 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058738-240626123714530/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.26530554
title: Compressibility effects on Rayleigh-Taylor instability in magnetized strongly coupled dusty plasma

description: The compressibility effects have been studied on the internal wave modes and Rayleigh-Taylor (R-T) instability in a magnetized strongly coupled dusty plasma (SCDP). A dusty fluid model is constructed considering the effects of weakly coupled electrons/ions and strongly coupled dust grains under the influence of the gravitational field. The effects of the magnetic field and viscoelastic coefficients have been incorporated under the generalized hydrodynamic (GH) fluid description in a quasineutral dusty plasma. The dispersion relation of R-T instability is derived analytically and discussed in the strongly coupled limit. The compressibility effects have appeared in the internal wave modes, significantly modifying the R-T instability criterion and growth rates. The Coulomb coupling parameter and dust magnetosonic speed suppress the growth rate of the R-T instability in a compressible SCDP.
DOI: 10.6084/m9.figshare.26530554.v1
title: Compressibility effects on Rayleigh-Taylor instability in magnetized strongly coupled dusty plasma

description: The compressibility effects have been studied on the internal wave modes and Rayleigh-Taylor (R-T) instability in a magnetized strongly coupled dusty plasma (SCDP). A dusty fluid model is constructed considering the effects of weakly coupled electrons/ions and strongly coupled dust grains under the influence of the gravitational field. The effects of the magnetic field and viscoelastic coefficients have been incorporated under the generalized hydrodynamic (GH) fluid description in a quasineutral dusty plasma. The dispersion relation of R-T instability is derived analytically and discussed in the strongly coupled limit. The compressibility effects have appeared in the internal wave modes, significantly modifying the R-T instability criterion and growth rates. The Coulomb coupling parameter and dust magnetosonic speed suppress the growth rate of the R-T instability in a compressible SCDP.
DOI: 10.6084/m9.figshare.26530560
title: Automated labelling and correlation analysis of diagnostic signals from ADITYA tokamak for developing AI-based disruption mitigation systems

description: AI/ML-based data-driven methodologies are becoming increasingly effective in understanding and predicting plasma disruption in tokamaks by identifying critical signatures present in various diagnostic signals obtained from tokamaks. A high-performance ML-based disruption predictor requires large accurately labelled data. Until now, plasma shots from the ADITYA tokamak have primarily been classified (labelled) as disruptive or non-disruptive manually. Here, we present three computational techniques, namely the Sorted-array approach, the Interval comparison approach and the Threshold-Straight line method for automatic labelling of the ADITYA shots as disruptive or non-disruptive based on the plasma current dropdown time. Statistical analysis and comparison between automatic labelling and manual labelling indicate the promising potential of the proposed techniques. A correlation analysis is also conducted by incorporating plasma diagnostics such as Plasma current, Loop voltage, Bolometer, Mirnov, Hard X-ray, Soft–X-ray, Radiation from Hydrogen-alpha, ionised oxygen and ionised carbon. This comprehensive study offers valuable insights into diverse physical phenomena associated with disruptions. Furthermore, correlation analysis based on current quench time highlights the significance of different diagnostics in providing distinct signatures related to plasma disruption. The insights obtained from this work can play a pivotal role in advancing the development of data-driven disruption prediction systems for ADITYA tokamak.
DOI: 10.6084/m9.figshare.26530560.v1
title: Automated labelling and correlation analysis of diagnostic signals from ADITYA tokamak for developing AI-based disruption mitigation systems

description: AI/ML-based data-driven methodologies are becoming increasingly effective in understanding and predicting plasma disruption in tokamaks by identifying critical signatures present in various diagnostic signals obtained from tokamaks. A high-performance ML-based disruption predictor requires large accurately labelled data. Until now, plasma shots from the ADITYA tokamak have primarily been classified (labelled) as disruptive or non-disruptive manually. Here, we present three computational techniques, namely the Sorted-array approach, the Interval comparison approach and the Threshold-Straight line method for automatic labelling of the ADITYA shots as disruptive or non-disruptive based on the plasma current dropdown time. Statistical analysis and comparison between automatic labelling and manual labelling indicate the promising potential of the proposed techniques. A correlation analysis is also conducted by incorporating plasma diagnostics such as Plasma current, Loop voltage, Bolometer, Mirnov, Hard X-ray, Soft–X-ray, Radiation from Hydrogen-alpha, ionised oxygen and ionised carbon. This comprehensive study offers valuable insights into diverse physical phenomena associated with disruptions. Furthermore, correlation analysis based on current quench time highlights the significance of different diagnostics in providing distinct signatures related to plasma disruption. The insights obtained from this work can play a pivotal role in advancing the development of data-driven disruption prediction systems for ADITYA tokamak.
DOI: 10.15468/dl.54ug3e
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.895019 -33.550523, 148.895019 -33.555015, 148.897265 -33.555015, 148.897265 -33.550523, 148.895019 -33.550523))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058739-240626123714530/datasets/export for details.
DOI: 10.15468/dl.mzbfp7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.904002 -33.550523, 148.904002 -33.557261, 148.906248 -33.557261, 148.906248 -33.550523, 148.904002 -33.550523))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058741-240626123714530/datasets/export for details.
DOI: 10.15468/dl.525smb
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 "PublishingOrg is one of (3059a14b-7b43-41ce-beef-873999911dfe)",
 "TaxonKey is one of (Dendrobates truncatus (Cope, 1861))"
 ]
 }
 ]
}

 The dataset includes 22 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058740-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13284882
title: Data for Model Counting in the Wild (KR-24 paper)

description: Contents



Model Counting Benchmarks: Found in the zip file model_counting_benchmarks.zip.

Projected Counting Benchmarks: Found in the zip file projected_counting_benchmarks.zip.

Logfiles of Running counters: Stored in the logfiles.zip.

Binaries for Counters:  Provided in the archive: bins.zip.


Benchmarks

Each benchmark file is systematically prefixed to indicate its source or category as referenced in the paper. For example, benchmarks from the Network Reliability Benchmark Set are prefixed with netrel.

Logfiles

Logfiles are organized into folders corresponding to each counter used in the experiments.

Binaries

Contains binaries for each counter used in the experiments, along with a commands.txt file that provides instructions for running them.
DOI: 10.5281/zenodo.13284883
title: Data for Model Counting in the Wild (KR-24 paper)

description: Contents



Model Counting Benchmarks: Found in the zip file model_counting_benchmarks.zip.

Projected Counting Benchmarks: Found in the zip file projected_counting_benchmarks.zip.

Logfiles of Running counters: Stored in the logfiles.zip.

Binaries for Counters:  Provided in the archive: bins.zip.


Benchmarks

Each benchmark file is systematically prefixed to indicate its source or category as referenced in the paper. For example, benchmarks from the Network Reliability Benchmark Set are prefixed with netrel.

Logfiles

Logfiles are organized into folders corresponding to each counter used in the experiments.

Binaries

Contains binaries for each counter used in the experiments, along with a commands.txt file that provides instructions for running them.
DOI: 10.15468/dl.6uvsth
title: Occurrence Download

description: A dataset containing 107 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "PublishingOrg is one of (8483a1f0-1032-11db-ae00-b8a03c50a862, bc092ff0-02e4-11dc-991f-b8a03c50a862, f9b67ad0-9c9b-11d9-b9db-b8a03c50a862, b4640710-8e03-11d8-b956-b8a03c50a862, cc6110c7-f75c-47c8-8931-f7dd3f324777, 6ea87510-0561-11d8-b851-b8a03c50a862, 66522820-055c-11d8-b84e-b8a03c50a862, 021121c0-f040-11d8-b22f-b8a03c50a862, ff90b050-c256-11db-b71b-b8a03c50a862, fd0038d0-3e7b-11d9-8439-b8a03c50a862, c76cf030-2a95-11da-9cc1-b8a03c50a862, b3bf3a83-1f68-4541-a03f-330d30d567f5, 396d5f30-dea9-11db-8ab4-b8a03c50a862, 7b8aff00-a9f8-11d8-944b-b8a03c50a862, a42867f0-813a-11dc-82e0-b8a03c50a862)",
 "TaxonKey is Melanoides tuberculata (O.F.Müller, 1774)"
 ]
}

 The dataset includes 107 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058742-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13287080
title: Chlamydomonas pacifica Lipid Transcription Factors

description: Contains the plasmid sequence for pJPCHx1_CpaDpWRI1, pJPCHx1_CpaAtWRI1, pJPCHx1_CpaMYB6, pJPCHx1_CpabZIP1, pJPCHx1_CpaSPL12, pJPCHx1_CpaPSR1, pJPCHx1_CpaCHT7, pJPCHx1_CpaNRR1, and pJPCHx1_CpaLRL1.
DOI: 10.5281/zenodo.13287081
title: Chlamydomonas pacifica Lipid Transcription Factors

description: Contains the plasmid sequence for pJPCHx1_CpaDpWRI1, pJPCHx1_CpaAtWRI1, pJPCHx1_CpaMYB6, pJPCHx1_CpabZIP1, pJPCHx1_CpaSPL12, pJPCHx1_CpaPSR1, pJPCHx1_CpaCHT7, pJPCHx1_CpaNRR1, and pJPCHx1_CpaLRL1.
DOI: 10.15468/dl.5umz5u
title: Occurrence Download

description: A dataset containing 176 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Balsamorhiza rosea A.Nelson & J.F.Macbr."
 ]
}

 The dataset includes 176 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058743-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yqsyj3
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "PublishingOrg is one of (8483a1f0-1032-11db-ae00-b8a03c50a862, bc092ff0-02e4-11dc-991f-b8a03c50a862, f9b67ad0-9c9b-11d9-b9db-b8a03c50a862, b4640710-8e03-11d8-b956-b8a03c50a862, cc6110c7-f75c-47c8-8931-f7dd3f324777, 6ea87510-0561-11d8-b851-b8a03c50a862, 66522820-055c-11d8-b84e-b8a03c50a862, 021121c0-f040-11d8-b22f-b8a03c50a862, ff90b050-c256-11db-b71b-b8a03c50a862, fd0038d0-3e7b-11d9-8439-b8a03c50a862, c76cf030-2a95-11da-9cc1-b8a03c50a862, b3bf3a83-1f68-4541-a03f-330d30d567f5, 396d5f30-dea9-11db-8ab4-b8a03c50a862, 7b8aff00-a9f8-11d8-944b-b8a03c50a862, a42867f0-813a-11dc-82e0-b8a03c50a862, c1da06f0-580e-11dc-8a9e-b8a03c50a862)",
 "TaxonKey is Radix auricularia (Linnaeus, 1758)"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058744-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fxy6jv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.687786 -33.550523, 149.687786 -33.555015, 149.694523 -33.555015, 149.694523 -33.550523, 149.687786 -33.550523))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058746-240626123714530/datasets/export for details.
DOI: 10.15468/dl.8t5x79
title: Occurrence Download

description: A dataset containing 2004336 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Milvus migrans (Boddaert, 1783)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 2004336 records from 3166 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058732-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.twtvp6
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Passiflora caerulea L.",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 16 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0186812-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zykwae
title: Occurrence Download

description: A dataset containing 2908 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Abelmoschus moschatus (L.) Medik."
 ]
}

 The dataset includes 2908 records from 177 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0275240-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7dr9sx
title: Occurrence Download

description: A dataset containing 503 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dendropanax trifidus (Thunb.) Makino ex H.Hara",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 503 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0186804-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.