cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7483/opendata.cms.1cad.rwqw
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.lytg.ynpy
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.pmf3.ir90
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.0i2n.zyqv
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.976m.im81
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.ull4.xyng
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.rwkk.i9v5
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.td2y.wu0f
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.zage.zll7
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.vf6u.j1vg
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.15468/dl.p8dmvu
title: Occurrence Download

description: A dataset containing 440 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is Canada",
 "TaxonKey is Mycena leaiana (Berk.) Sacc.",
 "DecimalLongitude is -79.3439314990000071,-63.9999979090000011",
 "DecimalLatitude is 45.0000682390000009, 50.0000022050000013"
 ]
}

 The dataset includes 440 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069972-241126133413365/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.fntu.nhpo
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.5281/zenodo.14649212
title: HAARP API experimental data 2014

description: Raw data corresponding to HF signals received during API experiment conducted at HAARP from Apr. 18, 2014.
DOI: 10.5281/zenodo.14649213
title: HAARP API experimental data 2014

description: Raw data corresponding to HF signals received during API experiment conducted at HAARP from Apr. 18, 2014.
DOI: 10.7483/opendata.cms.f2i3.effo
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.15468/dl.2chzj7
title: Occurrence Download

description: A dataset containing 249 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Barcant Butterfly Collection - Hesperiidae"
 ]
}

 The dataset includes 249 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069973-241126133413365/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.g8dm.t4cw
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.get2.nq08
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.bcfg.703v
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.7483/opendata.cms.qts4.jc51
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v3/NANOAODSIM
DOI: 10.15468/dl.g28bdh
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sumatroscirpus paniculatocorymbosus (Kük.) Lév.-Bourret & J.R.Starr"
 ]
}

 The dataset includes 30 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069974-241126133413365/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.ypmm.ftq2
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.lp81.jyt1
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-700_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.d1d2.w8u7
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.t18q.3xcu
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.gwdd.auxk
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.k0hf.lmsf
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.clw9.4qkn
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.i6qr.9aog
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.st8m.8oly
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.co37.dxbd
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.xtzc.eiwg
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.78yy.vdnw
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.15468/dl.xf8k8q
title: Occurrence Download

description: A dataset containing 506 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is Canada",
 "TaxonKey is Ischnoderma resinosum (Schrad.) P.Karst.",
 "DecimalLongitude is -79.3439314990000071,-63.9999979090000011",
 "DecimalLatitude is 45.0000682390000009, 50.0000022050000013"
 ]
}

 The dataset includes 506 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069976-241126133413365/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.y2sj.25pa
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.15468/dl.v2fm5y
title: Occurrence Download

description: A dataset containing 530 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is Canada",
 "TaxonKey is Artomyces pyxidatus (Pers.) Jülich",
 "DecimalLongitude is -79.3439314990000071,-63.9999979090000011",
 "DecimalLatitude is 45.0000682390000009, 50.0000022050000013"
 ]
}

 The dataset includes 530 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069975-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57841/casdc.0005072
title: 33个乡猪和大白猪单细胞转录组数据集
DOI: 10.6084/m9.figshare.28208414
title: ASI-GCN

description: Limited borehole sampling at contaminated sites results in sparse and unevenly distributed data on soil pollutants. Traditional interpolation methods, such as ordinary kriging (OK) and inverse distance weighting (IDW), may obscure local variations in soil contamination when applied to such sparse data, thus reducing the interpolation accuracy. To overcome this challenge, we propose an adaptive spatial interpolation graph convolutional network (ASI-GCN) model. This model synergistically integrated the principles of spatial auto-correlation with the capabilities of graph convolutional networks (GCN). By merging these elements, the ASI-GCN model effectively constrained the transfer of pollutant concentrations. It adeptly captures nuanced variations in spatial structure, thereby enhancing the precision of soil pollution characterization. We applied our model to a coking plant in Beijing based on 215 soil samples collected from 15 boreholes. To evaluate the robustness of the model, three pollutants with distinct volatilization characteristics were employed, including arsenic (As, non-volatile), benzo(a)pyrene (BaP, semi-volatile), and benzene (Ben, volatile). The leave-one-out cross-validation procedure was used to estimate the performance of ASI-GCN and its derivatives, ASI-GCN_RC_G and ASI-GCN_RC_K, when they are used to make predictions at unsampled sites.The results showed that the ASI-GCN model demonstrated improved performance with R² values of 0.52, 0.67, and 0.57, and RMSE values of 5.041 mg/kg, 1.699 mg/kg , and 167.710 mg/kg for As, BaP, and Ben, respectively, outperforming traditional models like OK and IDW. Further analysis revealed the significant influence of pollutant volatility on vertical migration patterns. Non-volatile As was primarily distributed in the fill and silty sand layers, semi-volatile BaP concentrated in the silty sand layer, while volatile Ben was predominantly found in the clay and fine sand layers. The ASI-GCN model provides key insights for risk assessment and remediation strategies by capturing complex contaminant distributions with limited borehole data, demonstrating its potential for application in various contaminated sites.
DOI: 10.7483/opendata.cms.mt5f.opkc
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.6084/m9.figshare.28208414.v1
title: ASI-GCN

description: Limited borehole sampling at contaminated sites results in sparse and unevenly distributed data on soil pollutants. Traditional interpolation methods, such as ordinary kriging (OK) and inverse distance weighting (IDW), may obscure local variations in soil contamination when applied to such sparse data, thus reducing the interpolation accuracy. To overcome this challenge, we propose an adaptive spatial interpolation graph convolutional network (ASI-GCN) model. This model synergistically integrated the principles of spatial auto-correlation with the capabilities of graph convolutional networks (GCN). By merging these elements, the ASI-GCN model effectively constrained the transfer of pollutant concentrations. It adeptly captures nuanced variations in spatial structure, thereby enhancing the precision of soil pollution characterization. We applied our model to a coking plant in Beijing based on 215 soil samples collected from 15 boreholes. To evaluate the robustness of the model, three pollutants with distinct volatilization characteristics were employed, including arsenic (As, non-volatile), benzo(a)pyrene (BaP, semi-volatile), and benzene (Ben, volatile). The leave-one-out cross-validation procedure was used to estimate the performance of ASI-GCN and its derivatives, ASI-GCN_RC_G and ASI-GCN_RC_K, when they are used to make predictions at unsampled sites.The results showed that the ASI-GCN model demonstrated improved performance with R² values of 0.52, 0.67, and 0.57, and RMSE values of 5.041 mg/kg, 1.699 mg/kg , and 167.710 mg/kg for As, BaP, and Ben, respectively, outperforming traditional models like OK and IDW. Further analysis revealed the significant influence of pollutant volatility on vertical migration patterns. Non-volatile As was primarily distributed in the fill and silty sand layers, semi-volatile BaP concentrated in the silty sand layer, while volatile Ben was predominantly found in the clay and fine sand layers. The ASI-GCN model provides key insights for risk assessment and remediation strategies by capturing complex contaminant distributions with limited borehole data, demonstrating its potential for application in various contaminated sites.
DOI: 10.7483/opendata.cms.k35d.iec7
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.vog4.zt2z
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.vqn2.7vx9
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-600_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.15468/dl.8vr9df
title: Occurrence Download

description: A dataset containing 433 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is Canada",
 "TaxonKey is Lycoperdon perlatum Pers.",
 "DecimalLongitude is -79.3439314990000071,-63.9999979090000011",
 "DecimalLatitude is 45.0000682390000009, 50.0000022050000013"
 ]
}

 The dataset includes 433 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069978-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sxt6rd
title: Occurrence Download

description: A dataset containing 458 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Barcant Butterfly Collection - Pieridae"
 ]
}

 The dataset includes 458 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069977-241126133413365/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.1crt.hegr
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-600_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.9fcl.hv4a
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.gukp.t7g8
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.rrjg.u0yk
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.ebx5.rf8m
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.8jv2.fdxp
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.00hn.c742
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.y0xu.mh64
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.px0u.ul7c
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-750_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.uzcy.tjz3
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.7afg.ubxi
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.c34c.lzxc
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.vyo1.bg1x
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.er0v.itry
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.2ly5.fvpl
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.nwd6.lf6d
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.bb14.2qzm
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.3tou.z4lu
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.zkeq.kkag
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.vi69.uldf
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.bk1m.spxc
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.jvpl.s9bs
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.57841/casdc.0005073
title: 9个宁乡猪单细胞转录组测序数据集
DOI: 10.7483/opendata.cms.rmq5.m9on
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.yrjl.tli4
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-600_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.0owl.p1e3
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-600_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.fsnt.fo55
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.7qbf.ixg6
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-60_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.ho1w.bnad
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.7vk4.5opc
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-70_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.fhqa.ia5j
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.15468/dl.pvr9fs
title: Occurrence Download

description: A dataset containing 173 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Barcant Butterfly Collection - Papilionidae"
 ]
}

 The dataset includes 173 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069979-241126133413365/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.5vwt.vyre
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-80_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.8mnb.xxlz
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.drkk.t54a
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-800_MY-90_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.eiy4.odss
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.p0q6.mhpg
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-100_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.g6pn.bu6k
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.373l.607j
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.4x3s.j9y0
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.9h28.uu8g
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.b3dn.iuiy
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.c9yl.9v38
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.zqm5.sewh
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.xlv5.oq6e
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-300_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.q69a.tx7m
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.bn7h.z1vj
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v2/NANOAODSIM
DOI: 10.7483/opendata.cms.1c7j.wozs
title: /NMSSM_XToYHTo2Z2BTo2L2Nu2B_MX-850_MY-500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM