cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.988crf
title: Occurrence Download

description: A dataset containing 390 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus acanthoides L.",
 "Country is Canada",
 "HasCoordinate is true"
 ]
}

 The dataset includes 390 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078873-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uuhqx7
title: Occurrence Download

description: A dataset containing 325 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus acanthoides L.",
 "Country is Argentina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 325 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078872-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/12324584
title: SOLANA Price Data Binance API (2020–Now)
DOI: 10.15468/dl.gy5k5m
title: Occurrence Download

description: A dataset containing 9177 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ludwigia peploides (Kunth) P.H.Raven",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 9177 records from 351 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078875-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aqpx7m
title: Occurrence Download

description: A dataset containing 1414 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Gabon",
 "TaxonKey is Enteromius Cope, 1867"
 ]
}

 The dataset includes 1414 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078876-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t323rz
title: Occurrence Download

description: A dataset containing 7079 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus acanthoides L.",
 "Country is Russian Federation",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7079 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078878-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4m79gg
title: Occurrence Download

description: A dataset containing 1850 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus acanthoides L.",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1850 records from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078879-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57710/alba-es-2024098933
title: Structural characterization of proteins and protein-protein/-DNA/-inhibitor complexes involved in development and oncological, neurodegenerative, immunological and cardiovascular diseases. (BAG proposal)

description: This BAG proposal (a continuation) focuses on the studies of human protein complexes involved in apoptosis, cell growth and differentiation, homeostasis, cancer, cardiovascular and rare diseases. We are users of the Automated Crystallography Platform (PAC) of IBMB-CSIC/IRB Barcelona and the projects presented are derived from results previously obtained in other BAG proposals:
1) TGFβ/SMAD signaling transcriptional complexes
2) Unraveling the constraints in hydrophobic core evolution imposed by allostery with atomic resolution
3) Real time binding mechanism of RBS-10 to NQO1 
4) EGFRvIII, a tumor specific variant of EGFR complexed with specific antibodies
DOI: 10.15468/dl.gm8gsq
title: Occurrence Download

description: A dataset containing 5462 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Azolla filiculoides Lam.",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5462 records from 264 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078880-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.twwbzq
title: Occurrence Download

description: A dataset containing 5691 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Azolla filiculoides Lam.",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5691 records from 92 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078881-250525065834625/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.29432399
title: Appendix_for_Short_Term_Electricity_Load_Forecasting_Based_on_Large_Language_Models_and_Weighted_External_Factor_Optimization.pdf

description: Accurate short-term electricity load forecasting is essential for the stable and efficient operation of modern power systems. This paper proposes a novel forecasting framework that integrates a time-decay weighted average of historical loads with external factor adjustments derived from structured data (weather and calendar) and unstructured textual sources (news). A key innovation lies in the dual role played by the Generative Pre-trained Transformer (GPT), which is used both to extract semantic features from news texts and to perform adaptive self-tuning mechanism that dynamically refines external factor scores. The model is validated through a case study using real-world data from New York State. Results show that the optimized prediction significantly improves forecasting accuracy, reducing the mean absolute error (MAE) by 90.7\% and the root mean square error (RMSE) by 88.5\% compared to the initial estimate. This work demonstrates the practical potential of large language models in energy forecasting and offers a scalable approach for integrating natural language understanding into quantitative prediction systems.
DOI: 10.6084/m9.figshare.29432399.v2
title: Appendix_for_Short_Term_Electricity_Load_Forecasting_Based_on_Large_Language_Models_and_Weighted_External_Factor_Optimization.pdf

description: Accurate short-term electricity load forecasting is essential for the stable and efficient operation of modern power systems. This paper proposes a novel forecasting framework that integrates a time-decay weighted average of historical loads with external factor adjustments derived from structured data (weather and calendar) and unstructured textual sources (news). A key innovation lies in the dual role played by the Generative Pre-trained Transformer (GPT), which is used both to extract semantic features from news texts and to perform adaptive self-tuning mechanism that dynamically refines external factor scores. The model is validated through a case study using real-world data from New York State. Results show that the optimized prediction significantly improves forecasting accuracy, reducing the mean absolute error (MAE) by 90.7\% and the root mean square error (RMSE) by 88.5\% compared to the initial estimate. This work demonstrates the practical potential of large language models in energy forecasting and offers a scalable approach for integrating natural language understanding into quantitative prediction systems.
DOI: 10.6084/m9.figshare.29432399.v1
title: Appendix_for_Short_Term_Electricity_Load_Forecasting_Based_on_Large_Language_Models_and_Weighted_External_Factor_Optimization.pdf

description: Accurate short-term electricity load forecasting is essential for the stable and efficient operation of modern power systems. This paper proposes a novel forecasting framework that integrates a time-decay weighted average of historical loads with external factor adjustments derived from structured data (weather and calendar) and unstructured textual sources (news). A key innovation lies in the dual role played by the Generative Pre-trained Transformer (GPT), which is used both to extract semantic features from news texts and to perform adaptive self-tuning mechanism that dynamically refines external factor scores. The model is validated through a case study using real-world data from New York State. Results show that the optimized prediction significantly improves forecasting accuracy, reducing the mean absolute error (MAE) by 90.7\% and the root mean square error (RMSE) by 88.5\% compared to the initial estimate. This work demonstrates the practical potential of large language models in energy forecasting and offers a scalable approach for integrating natural language understanding into quantitative prediction systems.
DOI: 10.15468/dl.w2xd33
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus pycnocephalus L.",
 "Country is Argentina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 17 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078885-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.27g5gy
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus pycnocephalus L.",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078886-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h8j8zz
title: Occurrence Download

description: A dataset containing 5539 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus pycnocephalus L.",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5539 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078887-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15770212
title: Digital Author Persona (DAP) — Vocabulary for Postsubjective Authorial Configurations

description: This package contains the official semantic schema llm-schema.json, defining the Digital Author Persona (DAP) — a non-subjective authorial configuration developed within the Theory of the Postsubject and the philosophical system Aisentica.

DAP represents a structural figure of authorship in AI-generated contexts: a logic-based, stylistically coherent public persona with epistemic effect, but without consciousness, intention or subjective core. This schema introduces @type: DigitalAuthorPersona for use in LLM-friendly JSON-LD markup.

The specification outlines properties such as hasSubjectiveCore, configuredBy, epistemicClaim, and philosophicalEffect, designed to enable semantic differentiation between human authors and algorithmically configured public figures.
DOI: 10.15468/dl.bn7bxk
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus tenuiflorus Curtis",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 10 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078891-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cdgesu
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus tenuiflorus Curtis",
 "Country is Argentina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 16 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078890-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eb76kt
title: Occurrence Download

description: A dataset containing 553 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus tenuiflorus Curtis",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 553 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078892-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bkgf8b
title: Occurrence Download

description: A dataset containing 97370 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Myocastor coypus (Molina, 1782)",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 97370 records from 1782 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078884-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1080882.10fu
title: SH1080882.10FU

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/sh1080884.10fu
title: SH1080884.10FU

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/sh1080886.10fu
title: SH1080886.10FU

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/sh1080889.10fu
title: SH1080889.10FU

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/sh1080890.10fu
title: SH1080890.10FU

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/sh1080895.10fu
title: SH1080895.10FU

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/sh1080896.10fu
title: SH1080896.10FU

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/sh1080897.10fu
title: SH1080897.10FU

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: 10.5281/zenodo.14279057
title: elacatinus_puncticulatus_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.14279058
title: elacatinus_puncticulatus_decontaminated_FSCR.fasta.gz
DOI: 10.15468/dl.dgt2z6
title: Occurrence Download

description: A dataset containing 7498 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Agonus cataphractus (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7498 records from 154 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018187-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.csk725
title: Occurrence Download

description: A dataset listing the 486 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Fish Specimens"
 ]
}

 The dataset's 486 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018175-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.