cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.rfq6s6
title: Occurrence Download

description: A dataset containing 136031 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "TaxonKey is Sprattus fuegensis"
 ]
}

 The dataset includes 136031 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004550-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8r8dg2
title: Occurrence Download

description: A dataset containing 2150170 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen, Observation)",
 "Geometry POLYGON((-95.58 34.42,-76.37 34.42,-76.37 37.29,-95.58 37.29,-95.58 34.42))",
 "License is one of (CC-BY-NC 4.0, CC-BY 4.0, CC0 1.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 2150170 records from 418 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004562-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/ju3kis
title: Mouse_0522_Na_Glu_GluData

description: Glu data
DOI: 10.17617/3.v4nsyb
title: Simulating Quadrupolar NMR Dynamics in Solid Electrolyte Li10GeP2S12

description: This folder contains simulation data for the submitted paper "T. Huss, F. Civaia, S. S. Köcher, K. Reuter, J. Granwehr and C. Scheurer, Simulating Quadrupolar NMR Dynamics in Solid Electrolyte Li10GeP2S12, 2025". Data includes the dataset for training of machine learning models, MD simulations and trajectories of predicted electric field gradient tensors.
DOI: 10.15468/dl.mdddyf
title: Occurrence Download

description: A dataset containing 1562 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bradypus variegatus",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1562 records from 96 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004646-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8bydqt
title: Occurrence Download

description: A dataset listing the 9960 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-70.45418 11.56314,-67.71122 11.56314,-67.71122 13.06067,-70.45418 13.06067,-70.45418 11.56314))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 9960 records were derived from 324 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004631-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.28083
title: Multi-spectral and single-shot wavefront detection technique based on neural networks
title: Multi-spectral and single-shot wavefront detection technique based on neural networks

description: Multi-spectral SHWFS spot pattern generationand neural network training programs.The Ten_sp_data.m (matlab) file generates SHWFS samples, with the target spectrum modifiable as required. The four_sp_resnet.py (python) file trains a model (using the ResNet50 architecture) on these samples to achieve synchronous measurement of multi-wavelength wavefronts.The data/label folder contains the label values for multiple sets of training and test samples. These labels can be used with the Ten_sp_data.m file to regenerate datasets or SHWFS patterns. The data/test_result folder also includes the testing set labels and the corresponding prediction errors.
description: Multi-spectral SHWFS spot pattern generationand neural network training programs.The Ten_sp_data.m (matlab) file generates SHWFS samples, with the target spectrum modifiable as required. The four_sp_resnet.py (python) file trains a model (using the ResNet50 architecture) on these samples to achieve synchronous measurement of multi-wavelength wavefronts.The data/label folder contains the label values for multiple sets of training and test samples. These labels can be used with the Ten_sp_data.m file to regenerate datasets or SHWFS patterns. The data/test_result folder also includes the testing set labels and the corresponding prediction errors.
DOI: 10.57760/sciencedb.29794
title: The Health Risks of Late-Night Marketing: How Staying Up Late Influences Consumer Trust Bias through Emotional Exhaustion and Psychological Compensation
title: The Health Risks of Late-Night Marketing: How Staying Up Late Influences Consumer Trust Bias through Emotional Exhaustion and Psychological Compensation

description: We collected data using an online survey. The questionnaire was distributed in October 2024 through a professional Chinese survey platform (e.g., Wenjuanxing). Our target participants were consumers in mainland China who had engaged in late-night (after 11:00 PM) online shopping or browsing commercial content in the past month. To ensure data quality, we included a screening question (“Have you engaged in any of the following activities after 11:00 PM in the past month?”) and an attention check (“Please select ‘Strongly Agree’ for this item”).
description: We collected data using an online survey. The questionnaire was distributed in October 2024 through a professional Chinese survey platform (e.g., Wenjuanxing). Our target participants were consumers in mainland China who had engaged in late-night (after 11:00 PM) online shopping or browsing commercial content in the past month. To ensure data quality, we included a screening question (“Have you engaged in any of the following activities after 11:00 PM in the past month?”) and an attention check (“Please select ‘Strongly Agree’ for this item”).
DOI: 10.6084/m9.figshare.25808698.v9
title: A global dataset of soil organic carbon mineralization under various incubation conditions

description: The dataset of "A global dataset of soil organic carbon mineralization under various incubation conditions"
DOI: 10.15468/dl.mgagz5
title: Occurrence Download

description: A dataset containing 1257 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "GadmGid is DEU.10.3_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Basidiomycota"
 ]
}

 The dataset includes 1257 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017816-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uwxz5g
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Casuariiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-100 -80,-90 -80,-90 -70,-100 -70,-100 -80))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017817-251009101135966/datasets/export for details.
DOI: 10.57760/sciencedb.28951
title: Dataset on the Effects of Nitrogen and Phosphorus on Adsorption, Dissolution, and Carbon Flux of Limestone Under Different Soil Depths
title: Dataset on the Effects of Nitrogen and Phosphorus on Adsorption, Dissolution, and Carbon Flux of Limestone Under Different Soil Depths

description: 《不同土层深度下氮磷对石灰石吸附、溶解和碳通量的影响》一文的参考资料和原始数据（包括DOI）
description: 《不同土层深度下氮磷对石灰石吸附、溶解和碳通量的影响》一文的参考资料和原始数据（包括DOI）
DOI: 10.15468/dl.u7zt7t
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tinamiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((60 -40,70 -40,70 -30,60 -30,60 -40))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017818-251009101135966/datasets/export for details.
DOI: 10.15468/dl.9zbmeu
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Casuariiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-110 -80,-100 -80,-100 -70,-110 -70,-110 -80))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017820-251009101135966/datasets/export for details.
DOI: 10.15468/dl.zdena3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tinamiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((70 -40,80 -40,80 -30,70 -30,70 -40))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017821-251009101135966/datasets/export for details.
DOI: 10.57760/sciencedb.29777
title: The original data related to “The Psychological Connotations and Empirical Examination of the ‘Lying Flat’ Phenomenon Among Chinese University Students”
title: 中国大学生躺平现象的心理内涵与实证检验相关原始数据

description: The interview transcripts were generated during Study 1, which involved in-depth interviews with 45 university students. All participants were anonymized and assigned coded identifiers.The quantitative research data were obtained from Studies 2, 3, and 4. These include exploratory factor analysis data based on 262 valid questionnaires; confirmatory factor analysis data based on 1,560 valid questionnaires; and data used for Studies 3 and 4, consisting of 2,323 valid questionnaires in total.The 17 questionnaire items and their corresponding dimensions are presented in the dataset.The original text of the informed consent form is also included in the dataset.
description: The interview transcripts were generated during Study 1, which involved in-depth interviews with 45 university students. All participants were anonymized and assigned coded identifiers.The quantitative research data were obtained from Studies 2, 3, and 4. These include exploratory factor analysis data based on 262 valid questionnaires; confirmatory factor analysis data based on 1,560 valid questionnaires; and data used for Studies 3 and 4, consisting of 2,323 valid questionnaires in total.The 17 questionnaire items and their corresponding dimensions are presented in the dataset.The original text of the informed consent form is also included in the dataset.
DOI: 10.6084/m9.figshare.30353326
title: ASC Hypothesis — Reproducibility Dataset (proofs, CI, HEP configs)

description: This dataset contains everything needed to reproduce the results of the paper“Asymmetric Self-Consistency Hypothesis: AI-Assisted Verification andFalsifiability” (DOI 10.6084/m9.figshare.30353320).<br>Contents (top-level)• README.md — quick start and structure• checksums.txt — SHA-256 for all files• Dockerfile — reproducible environment (Ubuntu 22.04 + Lean 4.0 + Coq 8.14 + Python)• proofs/ - Proofs.lean, AdjustedProof.lean — Lean scripts - Proofs.v, AdjustedProof.v — Coq scripts - gpt_report.json — AI verification summary - gpt_verify.py, cross_diff.py — verification helpers - adversarial/ — deliberately corrupted variants for stress tests• configs/ (if present) — HL-LHC and FCC-hh YAML configs• run_all.sh, run_delphes.py — batch/analysis helpers• figures/ — theory_blueband_cms.png, theory_blueband_moedal.png, exclusion_overlay.png, gpt_checker_summary.png• utils: check_images.py, generate_plots.py, etc.<br>How to reproduce (short)1) Build container: docker build -t asc_env .2) Run Lean/Coq inside container: docker run --rm -it -v $(pwd)/proofs:/workspace/proofs asc_env /bin/bash cd /workspace/proofs lean --make Proofs.lean && lean --make AdjustedProof.lean coqc Proofs.v && coqc AdjustedProof.v3) Validate GPT report: python3 gpt_verify.py --input gpt_report.json4) (Optional) Collider sim: cd /workspace python3 run_delphes.py --config configs/hl_lhc.yaml python3 run_delphes.py --config configs/fcc_hh.yaml5) Verify checksums: sha256sum -c checksums.txt<br>Notes• Licence for the dataset item is CC BY 4.0. Individual source files may additionally include a permissive software licence header when applicable.• No confidential or personal data included.<br>Recommended citationPSBigBig (2025). ASC Hypothesis — Reproducibility Dataset (proofs, CI, HEPconfigs). figshare. https://doi.org/10.6084/m9.figshare.30353326<br>Contacthello@onestardao.com<br>
DOI: 10.6084/m9.figshare.30353326.v1
title: ASC Hypothesis — Reproducibility Dataset (proofs, CI, HEP configs)

description: This dataset contains everything needed to reproduce the results of the paper“Asymmetric Self-Consistency Hypothesis: AI-Assisted Verification andFalsifiability” (DOI 10.6084/m9.figshare.30353320).<br>Contents (top-level)• README.md — quick start and structure• checksums.txt — SHA-256 for all files• Dockerfile — reproducible environment (Ubuntu 22.04 + Lean 4.0 + Coq 8.14 + Python)• proofs/ - Proofs.lean, AdjustedProof.lean — Lean scripts - Proofs.v, AdjustedProof.v — Coq scripts - gpt_report.json — AI verification summary - gpt_verify.py, cross_diff.py — verification helpers - adversarial/ — deliberately corrupted variants for stress tests• configs/ (if present) — HL-LHC and FCC-hh YAML configs• run_all.sh, run_delphes.py — batch/analysis helpers• figures/ — theory_blueband_cms.png, theory_blueband_moedal.png, exclusion_overlay.png, gpt_checker_summary.png• utils: check_images.py, generate_plots.py, etc.<br>How to reproduce (short)1) Build container: docker build -t asc_env .2) Run Lean/Coq inside container: docker run --rm -it -v $(pwd)/proofs:/workspace/proofs asc_env /bin/bash cd /workspace/proofs lean --make Proofs.lean && lean --make AdjustedProof.lean coqc Proofs.v && coqc AdjustedProof.v3) Validate GPT report: python3 gpt_verify.py --input gpt_report.json4) (Optional) Collider sim: cd /workspace python3 run_delphes.py --config configs/hl_lhc.yaml python3 run_delphes.py --config configs/fcc_hh.yaml5) Verify checksums: sha256sum -c checksums.txt<br>Notes• Licence for the dataset item is CC BY 4.0. Individual source files may additionally include a permissive software licence header when applicable.• No confidential or personal data included.<br>Recommended citationPSBigBig (2025). ASC Hypothesis — Reproducibility Dataset (proofs, CI, HEPconfigs). figshare. https://doi.org/10.6084/m9.figshare.30353326<br>Contacthello@onestardao.com<br>
DOI: 10.15468/dl.s77x2p
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amynthas minimus",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017822-251009101135966/datasets/export for details.
DOI: 10.57760/sciencedb.29062
title: body-related embarrassment，reliability，validity，college students
title: 身体尴尬量表，大学生，信度，效度

description: for body embarrassment scale-Chinese version
description: for body embarrassment scale-Chinese version
DOI: 10.18150/rb78j7
title: NMR Data and processing scripts for: Real-time monitoring of photoinduced atom transfer radical polymerization by Time-Resolved Diffusion NMR

description: Raw NMR Dataset used in the manuscript: Real-time monitoring of photoinduced atom transfer radical polymerization by Time-Resolved Diffusion NMR
DOI: 10.15468/dl.r6tsxu
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amynthas minimus",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017823-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.29813
title: The Influence of the Placement of Emoji in Social Networks on Emotional Contagion
title: 社交网络符号emoji的注意位置对情绪感染的影响

description: Experimental data in the paper 
description: Experimental data in the paper
DOI: 10.15468/dl.y5ywuc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tinamiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((80 -40,90 -40,90 -30,80 -30,80 -40))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017824-251009101135966/datasets/export for details.
DOI: 10.57760/sciencedb.29591
title: Rodents , cytb, mitochondrion
title: Rodents , cytb, mitochondrion

description: Total DNA was extracted from the feces using the QIAamp DNA Stool Mini Kit (QIAGEN, Germany), following the manufacturer’s protocol. Based on the complete mitochondria DNA (mtDNA) of N. confucianus (NC_023960.1) and A. agrarius (HM034866.1), we designed the primer (forward primer: ACTAATGACATGAAAAATCATCGTT; reverse-primer: TTCTTCATTTTTGGTTTACAAGACC) for the CYTB region using Primer Premier (V 5.0). We used the ABI3730XL gene analyzer (PE Applied Biosystems, USA) for bidirectional gene sequencing. Assembled sequences were subjected to BLAST analysis against the NCBI (National Center for Biotechnology Information) database, and species identification was determined using a percent identity threshold (PI) and query coverage (QC). 
description: Total DNA was extracted from the feces using the QIAamp DNA Stool Mini Kit (QIAGEN, Germany), following the manufacturer’s protocol. Based on the complete mitochondria DNA (mtDNA) of N. confucianus (NC_023960.1) and A. agrarius (HM034866.1), we designed the primer (forward primer: ACTAATGACATGAAAAATCATCGTT; reverse-primer: TTCTTCATTTTTGGTTTACAAGACC) for the CYTB region using Primer Premier (V 5.0). We used the ABI3730XL gene analyzer (PE Applied Biosystems, USA) for bidirectional gene sequencing. Assembled sequences were subjected to BLAST analysis against the NCBI (National Center for Biotechnology Information) database, and species identification was determined using a percent identity threshold (PI) and query coverage (QC).
DOI: 10.57760/sciencedb.29670
title: Resequencing data for Capsella bursa-pastoris
title: Resequencing data for Capsella bursa-pastoris

description: The aim of this study is to investigate the population genetic structure of these Capsella bursa-pastoris accessions and to uncover the genetic basis underlying adaptation to high-altitude environments.
description: The aim of this study is to investigate the population genetic structure of these Capsella bursa-pastoris accessions and to uncover the genetic basis underlying adaptation to high-altitude environments.
DOI: 10.15468/dl.xm47e6
title: Occurrence Download

description: A dataset containing 2344 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tetraclinis articulata"
 ]
}

 The dataset includes 2344 records from 153 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017825-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.65bzbt
title: Occurrence Download

description: A dataset containing 58 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Hebe subalpina)"
 ]
}

 The dataset includes 58 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017826-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wkx3sy
title: Occurrence Download

description: A dataset containing 0 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 GBIF_EEARGCODE(50000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000)) eeacellcode,
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, GBIF_EEARGCODE(50000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000)), "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, GBIF_EEARGCODE(50000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000)), "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, GBIF_EEARGCODE(50000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000)), "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, GBIF_EEARGCODE(50000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000)), "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, GBIF_EEARGCODE(50000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000)), "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, GBIF_EEARGCODE(50000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000)), "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.datasetkey = 'c779b049-28f3-4daf-bbf4-0a40830819b6'
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL AND occurrence.hascoordinate = TRUE)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year",
 GBIF_EEARGCODE(50000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000))

 The dataset's 0 records were derived from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017813-251009101135966/datasets/export for details.