cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.g5erbe
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Prosopis rojasiana"
 ]
}

 The dataset includes 48 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007417-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wmhe9s
title: Occurrence Download

description: A dataset containing 84 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Mexico",
 "TaxonKey is Crotalus ornatus",
 "Year 1960-2026"
 ]
}

 The dataset includes 84 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007416-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17984604
title: Fossil fuel CO2 Emissions in China (2015–2023) Inferred from Co-emitted NO2 Observations

description: Accurate quantification of China’s fossil fuel CO2 (FFCO2) emissions interannual variations is critical for climate policy evaluation. However, bottom-up inventories have exhibited increasing discrepancies. Here, we estimate 2015–2023 FFCO2 emissions over China using the Regional multi-Air Pollutant Assimilation System (RAPAS), integrating in-situ observations of co-emitted NO2 and grid-specific CO2-to-NOx ratios. National total FFCO2 averaged 11.5 ± 1.5 PgCO2·yr⁻¹, with over 45% from North (NC) and East China. Emission intensity (per GDP) exhibited a southeast-to-northwest increasing gradient, aligning with economic development patterns. Interannually, emissions showed a notable upward trend during 2015–2017 driven by NC and Central China, then stabilized during 2018–2023 amid policy interventions and COVID-19 disruptions, contrasting with sustained growth in widely used bottom-up inventories. Total annual growth averaged 189.6 TgCO2·yr-1 (1.6%). NC grew fastest at 73.0 TgCO2·yr⁻¹, while Southwest China declined slightly. Emission intensity fell 5.6% annually, with the largest drops in Southwest China (8.9%). This observation-constrained dataset clarifies spatiotemporal dynamics and policy impacts, supporting targeted strategies for China’s carbon goals.

 

FFCO2_NOx_Emissions_2015-2023.nc

Contains the optimized monthly fossil fuel CO₂ (FFCO₂) and NOₓ emissions over China during 2015–2023.

NO2_SRUFCONC_2015-2023.nc

Contains the optimized daily surface-layer NO₂ concentrations over China during 2015–2023.
DOI: 10.5281/zenodo.17984603
title: Fossil fuel CO2 Emissions in China (2015–2023) Inferred from Co-emitted NO2 Observations

description: Accurate quantification of China’s fossil fuel CO2 (FFCO2) emissions interannual variations is critical for climate policy evaluation. However, bottom-up inventories have exhibited increasing discrepancies. Here, we estimate 2015–2023 FFCO2 emissions over China using the Regional multi-Air Pollutant Assimilation System (RAPAS), integrating in-situ observations of co-emitted NO2 and grid-specific CO2-to-NOx ratios. National total FFCO2 averaged 11.5 ± 1.5 PgCO2·yr⁻¹, with over 45% from North (NC) and East China. Emission intensity (per GDP) exhibited a southeast-to-northwest increasing gradient, aligning with economic development patterns. Interannually, emissions showed a notable upward trend during 2015–2017 driven by NC and Central China, then stabilized during 2018–2023 amid policy interventions and COVID-19 disruptions, contrasting with sustained growth in widely used bottom-up inventories. Total annual growth averaged 189.6 TgCO2·yr-1 (1.6%). NC grew fastest at 73.0 TgCO2·yr⁻¹, while Southwest China declined slightly. Emission intensity fell 5.6% annually, with the largest drops in Southwest China (8.9%). This observation-constrained dataset clarifies spatiotemporal dynamics and policy impacts, supporting targeted strategies for China’s carbon goals.

 

FFCO2_NOx_Emissions_2015-2023.nc

Contains the optimized monthly fossil fuel CO₂ (FFCO₂) and NOₓ emissions over China during 2015–2023.

NO2_SRUFCONC_2015-2023.nc

Contains the optimized daily surface-layer NO₂ concentrations over China during 2015–2023.
DOI: 10.25574/cdc.486
title: Chandra X-ray Observatory Chandra Data Collection for request #486

description: Chandra Data Collection for request #486
description: DOI updated to include the publication's DOI on 2026-01-23-11:00:00
DOI: 10.15468/dl.36pkr2
title: Occurrence Download

description: A dataset containing 28372 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bufotes viridis",
 "Country is one of (Albania, Austria, Bosnia and Herzegovina, Belgium, Bulgaria, Belarus, Switzerland, Cyprus, Czechia, Germany, Denmark, Estonia, Spain, Finland, France, United Kingdom of Great Britain and Northern Ireland, Greece, Croatia, Hungary, Ireland, Italy, Lithuania, Luxembourg, Latvia, Moldova, Republic of, Montenegro, North Macedonia, Malta, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Sweden, Slovenia, Slovakia, Türkiye, Ukraine, Kosovo)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 28372 records from 189 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007418-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5v53z6
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Actinolema eryngioides",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 11 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007420-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18351679
title: Follow-up of young adults from a rural northern Pakistani village

description: These data come from a follow-up to a 1989-1996 study of diarrhea and pneumonia in children under age 5 years. The aim was to examine individual-level associations between childhood health and family socioeconomic indicators of early life adversity with adolescent health and development.
DOI: 10.5281/zenodo.18350461
title: Dataset for "Managing the Legacy: Geochemical Constraints and Heritage Conflicts in the Remediation of Zn-Pb-Ag Tailings at a UNESCO World Heritage Site"

description: This is a companion dataset to the paper by Cabała et al., submitted to Scientific Reports

 

 

The dataset is published under the Creative Commons Attribution 4.0 International License (CC-BY-4.0).

This license allows others to distribute, remix, adapt, and build upon the dataset for any purpose, even commercially, as long as they give appropriate credit to the original creator(s).

 

The dataset contains the following parts:

Table S1 Quality control/quality assurance (QC/QA) of the analytical procedure using the certified reference materials

Table S2: The chemical composition of the samples

Table S3: Leaching test results and summary of the Tessier et al. (1979) sequential extraction procedure.

Figure S1: Diffraction patterns of samples from Tarnowskie Góry
DOI: 10.5281/zenodo.18350462
title: Dataset for "Managing the Legacy: Geochemical Constraints and Heritage Conflicts in the Remediation of Zn-Pb-Ag Tailings at a UNESCO World Heritage Site"

description: This is a companion dataset to the paper by Cabała et al., submitted to Scientific Reports

 

 

The dataset is published under the Creative Commons Attribution 4.0 International License (CC-BY-4.0).

This license allows others to distribute, remix, adapt, and build upon the dataset for any purpose, even commercially, as long as they give appropriate credit to the original creator(s).

 

The dataset contains the following parts:

Table S1 Quality control/quality assurance (QC/QA) of the analytical procedure using the certified reference materials

Table S2: The chemical composition of the samples

Table S3: Leaching test results and summary of the Tessier et al. (1979) sequential extraction procedure.

Figure S1: Diffraction patterns of samples from Tarnowskie Góry
DOI: 10.5281/zenodo.18351787
title: ARTIFICIAL INTELLIGENCE IN ENGLISH LANGUAGE TEACHING

description: ArtificialIntelligence(AI)hasbecomeanincreasinglyinfluentialcomponentofmoderneducation,reshapingtraditionalapproachestoteachingandlearning.InEnglishLanguageTeaching(ELT),AItechnologiesofferinnovativesolutionsforpersonalizedinstruction,automatedassessment,andenhancedlearnerengagement.ThispaperprovidesacomprehensiveexaminationofAIinELT,exploringitstheoreticalfoundations,practicalapplications,benefits,challenges,andpedagogicalimplications.Italsodiscussestheevolvingroleofteachers,ethicalconsiderations,andfuturedirectionsforAI-enhancedlanguageeducation.ThestudyarguesthatwhileAIcannotreplacehumanteachers,itsthoughtfulintegrationcansignificantlyenrichEnglishlanguagelearningexperiences
DOI: 10.5281/zenodo.18351786
title: ARTIFICIAL INTELLIGENCE IN ENGLISH LANGUAGE TEACHING

description: ArtificialIntelligence(AI)hasbecomeanincreasinglyinfluentialcomponentofmoderneducation,reshapingtraditionalapproachestoteachingandlearning.InEnglishLanguageTeaching(ELT),AItechnologiesofferinnovativesolutionsforpersonalizedinstruction,automatedassessment,andenhancedlearnerengagement.ThispaperprovidesacomprehensiveexaminationofAIinELT,exploringitstheoreticalfoundations,practicalapplications,benefits,challenges,andpedagogicalimplications.Italsodiscussestheevolvingroleofteachers,ethicalconsiderations,andfuturedirectionsforAI-enhancedlanguageeducation.ThestudyarguesthatwhileAIcannotreplacehumanteachers,itsthoughtfulintegrationcansignificantlyenrichEnglishlanguagelearningexperiences
DOI: 10.15468/dl.4wfva3
title: Occurrence Download

description: A dataset containing 906 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pontederia hastata"
 ]
}

 The dataset includes 906 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007423-260120142942310/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.31083862
title: Cardiometabolic and Metabolic Profiles in Irritable Bowel Syndrome Associated with Type 2 Diabetes

description: Supplementary document for publishing on <i>American Journal of Physiology-Endocrinology and Metabolism</i> related to the research article "Cardiometabolic and Metabolic Profiles in Irritable Bowel Syndrome Associated with Type 2 Diabetes".<b>Abstract:</b> Irritable bowel syndrome (IBS), a common disorder of gut-brain interaction, has been increasingly associated with metabolic dysfunction and cardiometabolic risk. This study aimed to comprehensively assess cardiometabolic risk factors in individuals with IBS and to characterize their metabolic profiles in comparison with those of healthy and diabetic cohorts. First, in a retrospective database analysis, cardiometabolic risk factors of patients with IBS (n = 582,377) were compared with healthy controls (HC) (n = 1,492,376). Following propensity score matching (n = 492,468), cardiometabolic parameters were analyzed during a follow-up period of one to 24 months post-index. Second, a total of 234 individuals underwent comprehensive metabolic phenotyping utilizing state-of-the-art nuclear magnetic resonance spectroscopy, comparing blood profiles of patients diagnosed with type 2 diabetes (T2D), IBS, and HC. We observed an increased cardiometabolic risk profile in patients with IBS compared to HC, characterized by higher mean body mass index, higher triglyceride levels, lower high-density lipoprotein cholesterol, and higher hemoglobin A1c levels. Odds ratios (OR) were significantly increased in IBS, particularly for chronic hypergylcemia (OR = 16.32; p &lt; 0.001). Results were confirmed by deep metabolic phenotyping, revealing a metabolic tendency in IBS patients toward profiles characteristic of T2D by alterations in amino acid (glycine, histidine, phenylalanine), glucose (glucose, lactate, pyruvate), and lipid metabolism (parameters related to very low-density lipoproteins, VLDL). Our findings confirm that IBS is linked to a distinct cardiometabolic risk profile and reveal metabolic associations relevant to T2D.
DOI: 10.6084/m9.figshare.31083862.v1
title: Cardiometabolic and Metabolic Profiles in Irritable Bowel Syndrome Associated with Type 2 Diabetes

description: Supplementary document for publishing on <i>American Journal of Physiology-Endocrinology and Metabolism</i> related to the research article "Cardiometabolic and Metabolic Profiles in Irritable Bowel Syndrome Associated with Type 2 Diabetes".<b>Abstract:</b> Irritable bowel syndrome (IBS), a common disorder of gut-brain interaction, has been increasingly associated with metabolic dysfunction and cardiometabolic risk. This study aimed to comprehensively assess cardiometabolic risk factors in individuals with IBS and to characterize their metabolic profiles in comparison with those of healthy and diabetic cohorts. First, in a retrospective database analysis, cardiometabolic risk factors of patients with IBS (n = 582,377) were compared with healthy controls (HC) (n = 1,492,376). Following propensity score matching (n = 492,468), cardiometabolic parameters were analyzed during a follow-up period of one to 24 months post-index. Second, a total of 234 individuals underwent comprehensive metabolic phenotyping utilizing state-of-the-art nuclear magnetic resonance spectroscopy, comparing blood profiles of patients diagnosed with type 2 diabetes (T2D), IBS, and HC. We observed an increased cardiometabolic risk profile in patients with IBS compared to HC, characterized by higher mean body mass index, higher triglyceride levels, lower high-density lipoprotein cholesterol, and higher hemoglobin A1c levels. Odds ratios (OR) were significantly increased in IBS, particularly for chronic hypergylcemia (OR = 16.32; p &lt; 0.001). Results were confirmed by deep metabolic phenotyping, revealing a metabolic tendency in IBS patients toward profiles characteristic of T2D by alterations in amino acid (glycine, histidine, phenylalanine), glucose (glucose, lactate, pyruvate), and lipid metabolism (parameters related to very low-density lipoproteins, VLDL). Our findings confirm that IBS is linked to a distinct cardiometabolic risk profile and reveal metabolic associations relevant to T2D.
DOI: 10.5519/qd.ki6x8ynu
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5519/qd.her8x0j4
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.15468/dl.vwjnw3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.79533499999999 23.833744, 88.71856699999999 23.828167, 88.643708 23.811575, 88.572619 23.78438, 88.507064 23.747259, 88.448666 23.701133, 88.398865 23.647146, 88.358885 23.586638, 88.3297 23.521104, 88.312016 23.452165, 88.306251 23.381522, 88.312528 23.310916, 88.330674 23.242084, 88.360225 23.176717, 88.400441 23.116417, 88.450323 23.062663, 88.50864 23.01677, 88.573959 22.979858, 88.644682 22.95283, 88.71907899999999 22.936344, 88.79533499999999 22.930804, 88.871591 22.936344, 88.945988 22.95283, 89.016711 22.979858, 89.08203 23.01677, 89.14034700000001 23.062663, 89.190229 23.116417, 89.230445 23.176717, 89.259996 23.242084, 89.278142 23.310916, 89.284419 23.381522, 89.278654 23.452165, 89.26097 23.521104, 89.231785 23.586638, 89.191805 23.647146, 89.142004 23.701133, 89.083606 23.747259, 89.018051 23.78438, 88.946962 23.811575, 88.872103 23.828167, 88.79533499999999 23.833744))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007424-260120142942310/datasets/export for details.
DOI: 10.5281/zenodo.18351839
title: UZBEK MUSICAL INSTRUMENTS AND THEIR TYPES

description: Nowadays, only a small percentage of our people understand classical music, maqoms, and the performance of folk instruments in ensembles. There is a lack of knowledge about the history of our national instruments and their creation. Our youth and even adults do not know the names of our national instruments. For example, they refer to the Kashgar rubab as “dutor.” Sometimes we hear remarks like “Stop playing the ting-ring,” which shows a lack of understanding. Even schoolchildren are unaware of the names of our national instruments, such as the chang, ud, gijjak, doyra, flute, tanbur, rubab, qanun, and others, or of the famous performers associated with these instruments.Young people are more familiar with instruments like the guitar, electric organ, clarinet, accordion, and percussion instruments, rather than our traditional national instruments
DOI: 10.5281/zenodo.18351840
title: UZBEK MUSICAL INSTRUMENTS AND THEIR TYPES

description: Nowadays, only a small percentage of our people understand classical music, maqoms, and the performance of folk instruments in ensembles. There is a lack of knowledge about the history of our national instruments and their creation. Our youth and even adults do not know the names of our national instruments. For example, they refer to the Kashgar rubab as “dutor.” Sometimes we hear remarks like “Stop playing the ting-ring,” which shows a lack of understanding. Even schoolchildren are unaware of the names of our national instruments, such as the chang, ud, gijjak, doyra, flute, tanbur, rubab, qanun, and others, or of the famous performers associated with these instruments.Young people are more familiar with instruments like the guitar, electric organ, clarinet, accordion, and percussion instruments, rather than our traditional national instruments
DOI: 10.15468/dl.6myunh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.833538 24.094689, 88.756615 24.089112, 88.681606 24.07252, 88.61037399999999 24.045326, 88.54468900000001 24.008204, 88.486175 23.962078, 88.43627600000001 23.908092, 88.396218 23.847584, 88.366979 23.782052, 88.34926299999999 23.713114, 88.34348900000001 23.642474, 88.349782 23.57187, 88.36796699999999 23.503041, 88.397578 23.437677, 88.43787500000001 23.377381, 88.48785599999999 23.32363, 88.54628700000001 23.277739, 88.611734 23.24083, 88.68259399999999 23.213804, 88.75713500000001 23.19732, 88.833538 23.19178, 88.909941 23.19732, 88.984482 23.213804, 89.055342 23.24083, 89.120789 23.277739, 89.17922 23.32363, 89.229201 23.377381, 89.269498 23.437677, 89.299109 23.503041, 89.317294 23.57187, 89.323587 23.642474, 89.317813 23.713114, 89.30009699999999 23.782052, 89.270858 23.847584, 89.2308 23.908092, 89.18090100000001 23.962078, 89.122387 24.008204, 89.056702 24.045326, 88.98547000000001 24.07252, 88.910461 24.089112, 88.833538 24.094689))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007425-260120142942310/datasets/export for details.
DOI: 10.5517/ccdc.csd.cc2n22kd
title: CCDC 2444863: Experimental Crystal Structure Determination

description: Related Article: Nikolay V. Shcherbakov, Nathaniel Potin, Josep Mas-Roselló
|2026|ACS Catalysis|||doi:10.1021/acscatal.5c08127
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.z7z3xu
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Ecuador",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Myrcianthes hallii"
 ]
}

 The dataset includes 43 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007427-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n7qbu7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.786592 24.006145, 88.709722 24.000568, 88.634764 23.983976, 88.563581 23.956781, 88.49794 23.91966, 88.439465 23.873534, 88.3896 23.819547, 88.349569 23.759039, 88.320348 23.693506, 88.302643 23.624568, 88.29687199999999 23.553927, 88.30316000000001 23.483323, 88.321331 23.414493, 88.350922 23.349127, 88.39119100000001 23.28883, 88.441138 23.235078, 88.499531 23.189186, 88.56493399999999 23.152276, 88.63574699999999 23.125249, 88.710239 23.108765, 88.786592 23.103225, 88.862945 23.108765, 88.937437 23.125249, 89.00825 23.152276, 89.07365299999999 23.189186, 89.132046 23.235078, 89.18199300000001 23.28883, 89.222262 23.349127, 89.251853 23.414493, 89.27002400000001 23.483323, 89.276312 23.553927, 89.27054099999999 23.624568, 89.252836 23.693506, 89.223615 23.759039, 89.183584 23.819547, 89.133719 23.873534, 89.075244 23.91966, 89.009603 23.956781, 88.93841999999999 23.983976, 88.863462 24.000568, 88.786592 24.006145))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007426-260120142942310/datasets/export for details.
DOI: 10.25574/cdc.448
title: Chandra X-ray Observatory Chandra Data Collection for request #448

description: Chandra Data Collection for request #448
description: DOI updated to include the publication's DOI on 2026-01-23-11:00:00
DOI: 10.34847/nkl.809575d0
title: Décoloniser la géographie scolaire ? Colonialité, curriculum et pratiques : revue systématique (2000–2025)_Annexes

description: Revue Prisma_Annexe 1 : présentation résumée des 31 articles (objets, cadres théoriques, méthodologies)
description: Revue Prisma_Annexe 2 :explicitation des critères de regroupement des cadres théoriques
description: Revue Prisma : tableau d'extraction
DOI: 10.5281/zenodo.18349721
title: callopanchax_occidentalis_spades_01.fasta.gz
DOI: 10.5281/zenodo.18349720
title: callopanchax_occidentalis_spades_01.fasta.gz