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

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sempervivum iranicum Bornm. & Gauba"
 ]
}

 The dataset includes 16 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0123012-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.268pqe
title: Occurrence Download

description: A dataset containing 3129 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Zanthoxylum zanthoxyloides (Lam.) Zepern. & Timler"
 ]
}

 The dataset includes 3129 records from 95 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065886-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jtehtu
title: Occurrence Download

description: A dataset containing 77331 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Occurrence evidence, Observation)",
 "Country is United States of America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (VU, EN, CR)"
 ]
}

 The dataset includes 77331 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0145317-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8rtav4
title: Occurrence Download

description: A dataset containing 879540 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Nepal"
 ]
}

 The dataset includes 879540 records from 905 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0145325-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7483/opendata.cms.wh89.8ebo
title: /NMSSM_XToYHTo2Tau2B_MX-600_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.1jzp.jnvo
title: /NMSSM_XToYHTo2Tau2B_MX-600_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.69cd.e7nj
title: /NMSSM_XToYHTo2Tau2B_MX-600_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.4jc3.d3ct
title: /NMSSM_XToYHTo2Tau2B_MX-600_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.ve56.pk0h
title: /NMSSM_XToYHTo2Tau2B_MX-600_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.qxry.ybjh
title: /NMSSM_XToYHTo2Tau2B_MX-600_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.c98d.d3kw
title: /NMSSM_XToYHTo2Tau2B_MX-600_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.s8dt.tcaz
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.wnne.nkhz
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.s17x.gior
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.psmr.1e9b
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.gtaq.tgb0
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.3evi.aqrc
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.75mv.8q08
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.fs02.geg3
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.rnsv.tw4d
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.agpt.yq7y
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.j2nl.3ugf
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.oklr.lyu7
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.y9lq.410d
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.5281/zenodo.14648370
title: TCL38 PSet v1.1

description: This dataset, generated by the Aittokallio Lab, includes harmonised genetic, molecular and epigenetic data, with comprehensive annotations, and standardised drug response assessment of the cell lines, representing major clinical T-cell lymphoma and leukemia (TCL) subtypes and capturing the molecular and phenotypic diversity of TCLs.
DOI: 10.5281/zenodo.14648371
title: TCL38 PSet v1.1

description: This dataset, generated by the Aittokallio Lab, includes harmonised genetic, molecular and epigenetic data, with comprehensive annotations, and standardised drug response assessment of the cell lines, representing major clinical T-cell lymphoma and leukemia (TCL) subtypes and capturing the molecular and phenotypic diversity of TCLs.
DOI: 10.7483/opendata.cms.y271.qavy
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.x22y.pwip
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.bug0.g32q
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.ycth.mnwn
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.bh19.if4e
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.kegi.y4de
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.nq5e.zawb
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.zij5.663i
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.9kjy.1jq1
title: /NMSSM_XToYHTo2Tau2B_MX-650_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.zv3y.i0ze
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.3grm.rczk
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.wmyl.2mme
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.agg4.daef
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.cx64.v8yk
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.lpnq.eq84
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.3hls.j5wd
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.vfwz.mrz0
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.tk1o.ex2b
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.o5no.2c0j
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.5999.ajmc
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.jdug.sdrl
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.e8x0.youe
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.gz60.mm30
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.k0dy.9g8p
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.sk4z.7wc2
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.15468/dl.vfmq26
title: Occurrence Download

description: A dataset containing 1408 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chrysuronia lilliae (Stone, 1917)"
 ]
}

 The dataset includes 1408 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069637-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7483/opendata.cms.wvfe.plhp
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.6084/m9.figshare.28207796
title: Ci.xlsx

description: supplemental material<br>
DOI: 10.6084/m9.figshare.28207796.v1
title: Ci.xlsx

description: supplemental material<br>
DOI: 10.7483/opendata.cms.409k.wzlc
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.rxsl.tz7i
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.53u7.tnrn
title: /NMSSM_XToYHTo2Tau2B_MX-700_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.uttd.7xef
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.1w7t.q3ac
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.tnga.s20q
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.c7xh.pzuq
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.tevn.lf0y
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.pgjc.7knr
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.pwrh.ilb8
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.ttnr.y4ad
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.mmf5.p3nf
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.jfyh.zq2b
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.p9i9.jigk
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.15468/dl.zqyg8d
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Material citation, Specimen, Fossil, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Coordinate rounded, Geodetic datum assumed WGS84, Country derived from coordinates, Continent derived from coordinates, Basis of record invalid, Occurrence status inferred from individual count)",
 "TaxonKey is Glyphis gangeticus (Müller & Henle, 1839)"
 ]
}

 The dataset includes 15 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069638-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7483/opendata.cms.gkst.i0ym
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.7kgh.h5gp
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.ip11.l19z
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.evsd.bwcv
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-600_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.6kd2.j6rt
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-600_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.6pdm.f3x2
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.15468/dl.knxykn
title: Occurrence Download

description: A dataset containing 77 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepidopyga lilliae Stone, 1917"
 ]
}

 The dataset includes 77 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069640-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7483/opendata.cms.ve0b.4v4r
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.pu93.9kgc
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.15468/dl.ch43yk
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepidopilum grevilleanum Mitt."
 ]
}

 The dataset includes 48 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069639-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8b8dje
title: Occurrence Download

description: A dataset listing the 2026 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is University of Texas, Biodiversity Center, Ichthyology Collection (TNHCi)"
 ]
}

 The dataset's 2026 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069626-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7483/opendata.cms.jdrb.guak
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.5cf3.z8sw
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.hdid.u86b
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.tp2g.3ttf
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.uz7i.6isk
title: /NMSSM_XToYHTo2Tau2B_MX-750_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.klb7.uoyj
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.ofzt.dr9t
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.w7gr.hj99
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.maf6.d0kv
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.xn2x.3735
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.j0c7.5p9k
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.vbds.5rwz
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.urw3.zm34
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.eefh.6k9z
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.w0c5.hk1p
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.59xo.sx0w
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.ob0d.yl7g
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.px9a.agq0
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.3lpo.jh1d
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.hs3s.ct11
title: /NMSSM_XToYHTo2Tau2B_MX-800_MY-600_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.5281/zenodo.14235237
title: Optimizing Deep Learning Models for Aflatoxin Detection: A Case of Artificial Intelligence-Driven Classified Groundnut Image Datasets for Postharvest Management

description: DATASET DESCRIPTION This dataset comprises a curated collection of classified groundnut images, specifically designed for deep learning applications in aflatoxin detection. The dataset is organized into four distinct categories: Healthy, Moldy, Insect-Infested, and Physiological Disorder, making it a vital resource for training AI and machine learning models aimed at advancing agricultural research. These classifications are crucial for the development of AI-driven solutions addressing aflatoxin contamination, enhancing crop quality assessments, and improving postharvest management practices.The dataset has been developed to support research in agricultural Artificial Intelligence (AI), machine learning (ML), and food safety, with a focus on aiding resource-constrained regions in combating postharvest losses due to contamination. By leveraging this dataset, researchers can contribute to safeguarding public health, promoting food security, and supporting smallholder farmers.

POTENTIAL APPLICATIONSThis dataset provides numerous opportunities for innovation in agriculture through AI and deep learning technologies. Its key applications include:Early Aflatoxin Detection: Facilitates the development of AI-powered models for prompt identification of aflatoxins in groundnuts, helping mitigate associated health risks.Postharvest Management Improvement: Enables the creation of innovative solutions to enhance storage, handling, and processing, reducing contamination and losses.Food Safety and Quality Assurance: Strengthens agricultural value chains by supporting the production of safe and high-quality food products.

BROADER IMPACTThis resource is invaluable for fostering AI innovation in agriculture, particularly in resource-limited environments. It addresses critical challenges such as postharvest losses and food contamination while contributing to global efforts in sustainable agricultural development. By utilizing this dataset, researchers can improve food security, support smallholder farmers, and drive advancements in agricultural practices that benefit both local and global communities.