cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/ssen5a/rrraym
title: HillHuberCCES2014.tab
DOI: 10.7910/dvn/ssen5a/rsdvly
title: HillHuberLucidLong_withweights.tab
DOI: 10.7910/dvn/ssen5a/ug4p0h
title: 04_03_Lucid_Plots.R
DOI: 10.7910/dvn/y0zuxq/eritk9
title: Reporting follow up_veterinary staff_1.28.2019.tab
DOI: 10.7910/dvn/cefzlv/b4v6qc
title: cfs_2017091900.pkl

description: :unav
DOI: 10.7910/dvn/cefzlv/ivi0ig
title: cfs_2016112800.pkl

description: :unav
DOI: 10.7910/dvn/cefzlv/rciibd
title: cfs_2015100300.pkl

description: :unav
DOI: 10.7910/dvn/ssen5a/4qmnvv
title: 01_CreateDirectoryStructureMoveFiles.do
DOI: 10.7910/dvn/ssen5a/fodjfl
title: 02_02_CCES2014_PerformCoreAnalysis.do
DOI: 10.7910/dvn/ssen5a/ux4gts
title: 02_01_CCES2014_CreateCodebook.do
DOI: 10.21227/27hh-ga74
title: Audio Steganalysis Dataset

description: The steganography and steganalysis of audio, especially compressed audio, have drawn increasing attention in recent years, and various algorithms are proposed. However, there is no standard public dataset for us to verify the efficiency of each proposed algorithm. Therefore, to promote the study field, we construct a dataset including 33038 stereo WAV audio clips with a sampling rate of 44.1 kHz and duration of 10s. And, all audio files are from the Internet through data crawling, which is for a better simulation of a real detection environment. The dataset is used for MP3 steganalysis at this stage. We provide corresponding MP3 encoder, LAME, and steganographic encoder, HCM, EECS and so on, which is developed based on LAME. What's more, some useful python scripts are supplied for samples make in batch. The dataset is still expanding, and we will include AAC, AMR and other audio formats in the future.Keywords: Audio, MP3, Steganalysis, Steganography
DOI: 10.7910/dvn/cefzlv/0tusfh
title: cfs_2016062700.pkl

description: :unav
DOI: 10.7910/dvn/cefzlv/lrywab
title: cfs_2014010900.pkl

description: :unav
DOI: 10.7910/dvn/cefzlv/rcwrjx
title: cfs_2013041800.pkl

description: :unav
DOI: 10.7910/dvn/o2edhy/fndizw
title: 3IE Tables for Report.do

description: :unav
DOI: 10.7910/dvn/o2edhy/rqpen6
title: KGFS_Data_Codebook.xls

description: :unav
DOI: 10.7910/dvn/o2edhy/zxjzbf
title: Survey_Data_3ie_Report.tab

description: :unav
DOI: 10.7910/dvn/cefzlv/dlkrie
title: cfs_2011090500.pkl

description: :unav
DOI: 10.7910/dvn/pcviw6/bnw02d
title: Supplemental Online Material.docx

description: Full results of moderation analysis.
DOI: 10.7910/dvn/coq65b/si8bzt
title: rcd_1990-2015.tab

description: The Rebel Contraband Dataset
DOI: 10.7910/dvn/agbpxs/qcjtz6
title: Experiment Questionnair.pdf

description: :unav
DOI: 10.7910/dvn/agbpxs/w3lucg
title: Household Questionnair.pdf

description: :unav
DOI: 10.7910/dvn/agbpxs/omethe
title: Community Questionnair.pdf

description: :unav
DOI: 10.7910/dvn/cpviof/aanhjd
title: city.tab
DOI: 10.7910/dvn/cpviof/7ilcl7
title: variables_generation.do

description: :unav
DOI: 10.7910/dvn/cpviof/8pl4ig
title: ABLZ_AJPS2018_Codebook.pdf

description: :unav
DOI: 10.7910/dvn/cpviof/hq9i2s
title: ReadMe.pdf

description: :unav
DOI: 10.7910/dvn/cpviof/jq3rgd
title: ABLZ_AJPS2018_replication.R

description: :unav
DOI: 10.7910/dvn/lenfvh/rbabop
title: 20190117_1029_MORPHO_GRID.csv

description: Simulation of the reaction-diffusion model, recording morphological indicators in time
DOI: 10.7910/dvn/lenfvh/yug8bc
title: 20190117_1029_GRID.csv

description: Simulation of the RBD model
DOI: 10.5517/ccdc.csd.cc20tqp8
title: CCDC 1871770: Experimental Crystal Structure Determination

description: Related Article: Hong Yu, Jia-Xing Yang, Ju-Qing Han, Peng-Fei Li, Yin-Ling Hou, Wen-Min Wang, Ming Fang|2019|New J.Chem.|43|8067|doi:10.1039/C8NJ05109G
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: 10.5517/ccdc.csd.cc20vqxj
title: CCDC 1872738: Experimental Crystal Structure Determination

description: Related Article: Büşra Kaya, Bahri Ülküseven, Onur Şahin, Zarife Sibel Şahin|2019|J.Mol.Struct.|1191|337|doi:10.1016/j.molstruc.2019.04.079
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: 10.7910/dvn/o6pqtw/tdw2y3
title: Renata-Cavalcanti-script-tf-ad-ufpe-2018.R

description: :unav
DOI: 10.5517/ccdc.csd.cc1n97ck
title: CCDC 1528218: Experimental Crystal Structure Determination

description: Related Article: O.G. Shakirova, E.V. Korotaev, D.V. Evtushok, N.V. Kuratieva, L.A. Sheludyakova, M.A. Shestopalov, L.G. Lavrenova|2019|J.Mol.Struct.|1193|1|doi:10.1016/j.molstruc.2019.03.015
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: 10.5517/ccdc.csd.cc20w6x1
title: CCDC 1873203: Experimental Crystal Structure Determination

description: Related Article: Jiao-Xia Ma, Xu Fang, Min Xue, Yong Yang|2019|Org.Biomol.Chem.|17|5075|doi:10.1039/C9OB00613C
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: 10.5517/ccdc.csd.cc20w6y2
title: CCDC 1873204: Experimental Crystal Structure Determination

description: Related Article: Jiao-Xia Ma, Xu Fang, Min Xue, Yong Yang|2019|Org.Biomol.Chem.|17|5075|doi:10.1039/C9OB00613C
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: 10.5517/ccdc.csd.cc20wbpy
title: CCDC 1873320: Experimental Crystal Structure Determination

description: Related Article: Jiao-Xia Ma, Xu Fang, Min Xue, Yong Yang|2019|Org.Biomol.Chem.|17|5075|doi:10.1039/C9OB00613C
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: 10.5517/ccdc.csd.cc20wcr1
title: CCDC 1873353: Experimental Crystal Structure Determination

description: Related Article: O.G. Shakirova, E.V. Korotaev, D.V. Evtushok, N.V. Kuratieva, L.A. Sheludyakova, M.A. Shestopalov, L.G. Lavrenova|2019|J.Mol.Struct.|1193|1|doi:10.1016/j.molstruc.2019.03.015
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: 10.5517/ccdc.csd.cc20wcs2
title: CCDC 1873354: Experimental Crystal Structure Determination

description: Related Article: O.G. Shakirova, E.V. Korotaev, D.V. Evtushok, N.V. Kuratieva, L.A. Sheludyakova, M.A. Shestopalov, L.G. Lavrenova|2019|J.Mol.Struct.|1193|1|doi:10.1016/j.molstruc.2019.03.015
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: 10.7910/dvn/fpyktp/h0hilo
title: metadata-replications.yml
DOI: 10.7910/dvn/fpyktp/2v090r
title: data-weeks-2012.tab
DOI: 10.7910/dvn/fpyktp/ckwujt
title: data-weeks-2008.tab
DOI: 10.7910/dvn/fpyktp/fgks3d
title: data-sobek-abouharb-ingram-2006.tab
DOI: 10.7910/dvn/fpyktp/ncmkft
title: metadata-models.yml
DOI: 10.7910/dvn/fpyktp/yqwin6
title: data-zawahri-mitchell-2011.tab
DOI: 10.7910/dvn/fpyktp/g54azf
title: data-salehyan-2008-jop.tab
DOI: 10.7910/dvn/fpyktp/k0beta
title: data-reed-et-al-2008.tab
DOI: 10.7910/dvn/fpyktp/r8cod2
title: data-salehyan-2008-ajps.tab
DOI: 10.25606/surf.578c6039-37ef06db
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-712)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 712 of the 2048³ resolution collection.
DOI: 10.25606/surf.578c6039-f9fbd22a
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-721)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 721 of the 2048³ resolution collection.
DOI: 10.7910/dvn/fpyktp/rc32tf
title: data-park-colaresi-2014.tab
DOI: 10.7910/dvn/fpyktp/ypztdb
title: data-owsiak-2012.tab
DOI: 10.7910/dvn/fpyktp/i2svus
title: data-nmc-4.0.tab
DOI: 10.7910/dvn/fpyktp/pmrinq
title: data-midb-4.01.tab
DOI: 10.7910/dvn/fpyktp/ugzorm
title: data-morrow-2007.tab
DOI: 10.7910/dvn/fpyktp/ym0ygi
title: data-mida-4.01.tab
DOI: 10.7910/dvn/vy4tje/otq5jb
title: scholcommlab-rpt-master-january-2019.tab

description: Master file containing all observations, including names of institutions, institution types and subtypes, and indicates presence of each term or concept in the documents of each institution or academic unit.
DOI: 10.7910/dvn/vy4tje/syrqi0
title: scholcommlab-rpt-summary-tables-january-2019.tab

description: Several aggregations of the data found in the master table, by institution type, subtype, and disciplines.
DOI: 10.25606/surf.578c6039-49dce95d
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-703)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 703 of the 2048³ resolution collection.
DOI: 10.7910/dvn/fpyktp/6b6d85
title: data-fuhrmann-sechser-2014.tab
DOI: 10.7910/dvn/fpyktp/jynvcu
title: data-jung-2014.tab
DOI: 10.7910/dvn/fpyktp/kvz0rx
title: data-gartzke-2007.tab
DOI: 10.7910/dvn/fpyktp/p7rzeu
title: data-idealpoint4600.tab
DOI: 10.7910/dvn/vy4tje/x5n7v9
title: Data Dictionary and Methodology notes-january-2019.pdf

description: Data Dictionary and Methodology Notes
DOI: 10.25606/surf.578c6039-109221d0
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-711)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 711 of the 2048³ resolution collection.
DOI: 10.7910/dvn/fpyktp/s1xydq
title: data-fordham-2008.tab
DOI: 10.21227/4cca-rr50
title: Audio Steganalysis Dataset

description: The steganography and steganalysis of audio, especially compressed audio, have drawn increasing attention in recent years, and various algorithms are proposed. However, there is no standard public dataset for us to verify the efficiency of each proposed algorithm. Therefore, to promote the study field, we construct a dataset including 33038 stereo WAV audio clips with a sampling rate of 44.1 kHz and duration of 10s. And, all audio files are from the Internet through data crawling, which is for a better simulation of a real detection environment. The dataset is used for MP3 steganalysis at this stage. We provide corresponding MP3 encoder, LAME, and steganographic encoder, HCM, EECS and so on, which is developed based on LAME. What's more, some useful python scripts are supplied for samples make in batch. The dataset is still expanding, and we will include AAC, AMR and other audio formats in the future.Keywords: Audio, MP3, Steganalysis, Steganography
DOI: 10.7910/dvn/fpyktp/y1twsp
title: data-dreyer-2010.tab
DOI: 10.7910/dvn/fpyktp/nctjal
title: data-arena-palmer-2009.tab
DOI: 10.7910/dvn/fpyktp/p5uls7
title: predict-dyad.tab
DOI: 10.7910/dvn/fpyktp/qbddn6
title: predict-dir-dyad.tab
DOI: 10.7910/dvn/fpyktp/hdzq5c
title: fn-varimp.r
DOI: 10.7910/dvn/fpyktp/iybex2
title: fn-train.r
DOI: 10.7910/dvn/fpyktp/b42wic
title: fn-predict-from-ensemble.r
DOI: 10.7910/dvn/fpyktp/o3w19x
title: fn-merge-nmc-dyad.r
DOI: 10.7910/dvn/fpyktp/wutaml
title: fn-glm-and-cv.r
DOI: 10.7910/dvn/fpyktp/fwml7m
title: 400-collect-replications.r
DOI: 10.7910/dvn/fpyktp/gria4k
title: 401-describe-replications.r
DOI: 10.7910/dvn/fpyktp/jxnrrj
title: fn-defs-train.r
DOI: 10.7910/dvn/fpyktp/qfngai
title: fn-collect.r
DOI: 10.7910/dvn/fpyktp/ll1dsc
title: 315-weeks-2008.r
DOI: 10.7910/dvn/fpyktp/ohvkzh
title: 317-zawahri-mitchell-2011.r
DOI: 10.7910/dvn/fpyktp/xgqc1m
title: 316-weeks-2012.r
DOI: 10.7910/dvn/4gpttd/hiyy3s
title: VillageID2014_for_merge.tab
DOI: 10.7910/dvn/4gpttd/y2juhw
title: VillageID2013_for_merge.tab
DOI: 10.7910/dvn/fpyktp/0miobw
title: 313-sobek-abouharb-ingram-2006.r
DOI: 10.7910/dvn/fpyktp/neajfi
title: 312-salehyan-2008-jop.r
DOI: 10.7910/dvn/fpyktp/w4nr30
title: 311-salehyan-2008-ajps.r
DOI: 10.7910/dvn/fpyktp/bqnyxc
title: 307-jung-2014.r
DOI: 10.7910/dvn/fpyktp/qczsvt
title: 309-owsiak-2012.r
DOI: 10.7910/dvn/fpyktp/qpjgtu
title: 308-morrow-2007.r
DOI: 10.7910/dvn/fpyktp/qyspkb
title: 310-park-colaresi-2014.r
DOI: 10.7910/dvn/lenfvh/ot71tl
title: 20190117_1029_MORPHO_GRID.csv

description: Simulation of the reaction-diffusion model, recording morphological indicators in time
DOI: 10.7910/dvn/lenfvh/v6layo
title: 20190112_1620_LOCAL.csv

description: Simulation of the reaction-diffusion model, recording configuration distance between two independent runs from the same initial configuration
DOI: 10.7910/dvn/fpyktp/hftdzp
title: 303-fordham-2008.r
DOI: 10.7910/dvn/fpyktp/sskyqs
title: 304-fuhrmann-sechser-2014.r
DOI: 10.7910/dvn/fpyktp/yvvu43
title: 305-gartzke-2007.r
DOI: 10.7910/dvn/fpyktp/7okxk3
title: 114-summarize-varimp.r
DOI: 10.7910/dvn/fpyktp/fdhaeu
title: 302-dreyer-2010.r
DOI: 10.7910/dvn/fpyktp/fmd1ug
title: 200-reed-run-and-plot.r
DOI: 10.7910/dvn/fpyktp/jfp0ef
title: 300-arena-palmer-2009.r
DOI: 10.7910/dvn/fpyktp/coqge5
title: 113-collect-varimp.r
DOI: 10.7910/dvn/fpyktp/m4vxkv
title: 111-doe-vs-cinc.r
DOI: 10.7910/dvn/fpyktp/pijkag
title: 112-varimp.r
DOI: 10.7910/dvn/fpyktp/hnnwqu
title: 109-predict.r
DOI: 10.7910/dvn/fpyktp/jbajqf
title: 108-dir-dyad-year.r
DOI: 10.7910/dvn/fpyktp/vzelz4
title: 110-collect-predict.r
DOI: 10.7910/dvn/fpyktp/1knpwd
title: 106-summarize-weights.r
DOI: 10.7910/dvn/fpyktp/dezas1
title: 104-train-weights.r
DOI: 10.7910/dvn/fpyktp/skt7kk
title: 107-capratio.r
DOI: 10.7910/dvn/fpyktp/zha0ak
title: 105-collect-weights.r
DOI: 10.7910/dvn/fpyktp/8fqzrb
title: 102-outcomes-time.r
DOI: 10.7910/dvn/fpyktp/fduovc
title: 100-nmc.r
DOI: 10.7910/dvn/fpyktp/o1ucol
title: 101-mid.r
DOI: 10.7910/dvn/fpyktp/gksjpp
title: 000-install.r
DOI: 10.7910/dvn/fpyktp/lugwu5
title: _all.sh

description: :unav
DOI: 10.7910/dvn/pskduj/5ibglt
title: 2016-precinct-house.tab
DOI: 10.7910/dvn/rimktj/xyyrns
title: RevisedScaffolding.xlsx

description: Assessment instrument
DOI: 10.7910/dvn/o6pqtw/ku7z1d
title: pela2010.sav

description: database available for free on
DOI: 10.7910/dvn/o6pqtw/qaqpge
title: LAPOP_2010.tab

description: database available for free on
DOI: 10.7910/dvn/o6pqtw/qwbxnu
title: CavalcantiRenata_paperScript_InTheNameOfGod.R.R

description: :unav
DOI: 10.7910/dvn/o6pqtw/uzax0c
title: den_year.xlsx

description: Data about LGBTs situation in Brazil.
DOI: 10.7910/dvn/rimktj/u5zr0s
title: Data_DMS_Workshop_Assessments.xlsx

description: Data from assessment
DOI: 10.7910/dvn/mqppnc/cfsnpn
title: kerala-vision-ocr-output.tar.gz.partaa
DOI: 10.7910/dvn/mqppnc/faghgc
title: kerala-vision-ocr-output.tar.gz.partab
DOI: 10.7910/dvn/mqppnc/k2bday
title: kerala-vision-ocr-output.tar.gz.partac
DOI: 10.7910/dvn/mqppnc/wnx39d
title: kerala-vision-ocr-output.tar.gz.partad
DOI: 10.7910/dvn/o6pqtw/cyisse
title: CavalcantiRenata_paperScript_InTheNameOfGod.R

description: Script for replication
DOI: 10.7910/dvn/n4risx/66qwub
title: F75_Biochemistry.tab

description: This file contains biochemistry test results
DOI: 10.7910/dvn/n4risx/eyjh33
title: F75_SAEs.tab

description: This file contains all serious adevrse events like deaths (causes of deaths)
DOI: 10.7910/dvn/n4risx/fuomyr
title: F75_follow_up.tab

description: This file contains all follow-up data (at day 3, date of stabilisation and dsicharge from hospital)
DOI: 10.7910/dvn/n4risx/ibtsph
title: F75_Baseline_data.tab

description: This file contains baseline data including randomisation arm
DOI: 10.7910/dvn/n4risx/rdxvj6
title: Modified F75_Readme.txt

description: Readme File (txt)
DOI: 10.7910/dvn/n4risx/upbhv6
title: Modified_F75_data_Codebook.pdf

description: This file contains variable description, value labels and variable formats for all data files
DOI: 10.7910/dvn/n4risx/9frpij
title: F75_Daily_record.tab

description: This file contains daily obseravtions data for the days the participants were hospitalised
DOI: 10.7910/dvn/5xrzlh/hlbgzx
title: sources.json
DOI: 10.7910/dvn/ujrdig/1tdk9a
title: Ethiopia 2018.7z

description: Ethiopia Baseline Farm and Socio-Economic Data for Debra Zeit
DOI: 10.7910/dvn/r1hkvs/v4xags
title: README.txt

description: A description of the elements of the dataset
DOI: 10.7910/dvn/r1hkvs/bimqsb
title: timeline_0.jsonl

description: Mastodon timeline - Part 1
DOI: 10.7910/dvn/r1hkvs/btpjmt
title: timeline_5.jsonl

description: Mastodon timeline - Part 6
DOI: 10.7910/dvn/r1hkvs/ffstpl
title: timeline_1.jsonl

description: Mastodon timeline - Part 2
DOI: 10.7910/dvn/r1hkvs/iencdg
title: timeline_4.jsonl

description: Mastodon timeline - Part 5
DOI: 10.7910/dvn/r1hkvs/ijmtlg
title: metadata_descriptor.json

description: A description of the fields in toot and instance objects
DOI: 10.7910/dvn/r1hkvs/odiapx
title: timeline_2.jsonl

description: Mastodon timeline - Part 3
DOI: 10.7910/dvn/r1hkvs/rgqbur
title: timeline_3.jsonl

description: Mastodon timeline - Part 4
DOI: 10.7910/dvn/r1hkvs/vrg09f
title: instance_metadata.jsonl

description: The instance meta-data
DOI: 10.7910/dvn/ulhlcb/hfwhb3
title: articles.db.gz

description: Articles in sqlite database.
DOI: 10.7910/dvn/ulhlcb/uycet1
title: labels.csv

description: Source labels in csv format.
DOI: 10.7910/dvn/5xrzlh/hadss3
title: dataset.zip

description: :unav
DOI: 10.7910/dvn/ulhlcb/7z633z
title: labels.txt

description: Source labels in human readable format.