cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc28lqp9
title: CCDC 2103371: Experimental Crystal Structure Determination

description: Related Article: Jianfeng Wu, Serhiy Demeshko, Sebastian Dechert, Franc Meyer|2021|Dalton Trans.|50|17573|doi:10.1039/D1DT02815D
DOI: 10.5517/ccdc.csd.cc28lqqb
title: CCDC 2103372: Experimental Crystal Structure Determination

description: Related Article: Jianfeng Wu, Serhiy Demeshko, Sebastian Dechert, Franc Meyer|2021|Dalton Trans.|50|17573|doi:10.1039/D1DT02815D
DOI: 10.5517/ccdc.csd.cc28lqrc
title: CCDC 2103373: Experimental Crystal Structure Determination

description: Related Article: Jianfeng Wu, Serhiy Demeshko, Sebastian Dechert, Franc Meyer|2021|Dalton Trans.|50|17573|doi:10.1039/D1DT02815D
DOI: 10.5517/ccdc.csd.cc28lw5y
title: CCDC 2103510: Experimental Crystal Structure Determination

description: Related Article: Jian-Wei Zhang, Hui Li, Jie-Qiong Li, Ya Chen, Peng Qu, Quan-Guo Zhai|2021|Dalton Trans.|50|17482|doi:10.1039/D1DT03349B
DOI: 10.5517/ccdc.csd.cc28mv0s
title: CCDC 2104435: Experimental Crystal Structure Determination

description: Related Article: Yin Liu, Yicheng He, Yang Liu, Kun Wei, Wusheng Guo|2021|Org.Chem.Front.|8|7004|doi:10.1039/D1QO01405F
DOI: 10.5517/ccdc.csd.cc28nwkd
title: CCDC 2105444: Experimental Crystal Structure Determination

description: Related Article: Takefumi Kanno, Koji Nakabayashi, Kenta Imoto, Shin-ichi Ohkoshi|2021|Eur.J.Inorg.Chem.|2021|4681|doi:10.1002/ejic.202100747
DOI: 10.5517/ccdc.csd.cc28pdds
title: CCDC 2105935: Experimental Crystal Structure Determination

description: Related Article: Y.A. Kondratenko, A.A. Nikonorova, A.A. Zolotarev, M.Y. Arsent'ev, G.G. Nyanikova, V.L. Ugolkov, E.I. Sysoev, T.A. Kochina|2022|Inorg.Chim.Acta|530|120705|doi:10.1016/j.ica.2021.120705
DOI: 10.5517/ccdc.csd.cc28q1nq
title: CCDC 2106563: Experimental Crystal Structure Determination

description: Related Article: Steffen Maier, Nikolai Hippchen, Frank Rominger, Jan Freudenberg, Uwe H. F. Bunz|2021|Chem.-Eur.J.|27|16320|doi:10.1002/chem.202103193
DOI: 10.5517/ccdc.csd.cc28q1pr
title: CCDC 2106564: Experimental Crystal Structure Determination

description: Related Article: Steffen Maier, Nikolai Hippchen, Frank Rominger, Jan Freudenberg, Uwe H. F. Bunz|2021|Chem.-Eur.J.|27|16320|doi:10.1002/chem.202103193
DOI: 10.5517/ccdc.csd.cc28q1qs
title: CCDC 2106565: Experimental Crystal Structure Determination

description: Related Article: Steffen Maier, Nikolai Hippchen, Frank Rominger, Jan Freudenberg, Uwe H. F. Bunz|2021|Chem.-Eur.J.|27|16320|doi:10.1002/chem.202103193
DOI: 10.5517/ccdc.csd.cc28q1rt
title: CCDC 2106566: Experimental Crystal Structure Determination

description: Related Article: Steffen Maier, Nikolai Hippchen, Frank Rominger, Jan Freudenberg, Uwe H. F. Bunz|2021|Chem.-Eur.J.|27|16320|doi:10.1002/chem.202103193
DOI: 10.5517/ccdc.csd.cc28q1sv
title: CCDC 2106567: Experimental Crystal Structure Determination

description: Related Article: Steffen Maier, Nikolai Hippchen, Frank Rominger, Jan Freudenberg, Uwe H. F. Bunz|2021|Chem.-Eur.J.|27|16320|doi:10.1002/chem.202103193
DOI: 10.5517/ccdc.csd.cc28q2hl
title: CCDC 2106589: Experimental Crystal Structure Determination

description: Related Article: Yibin Zhou, Hao Tang, Zhao-Hui Li, Linxian Xu, Lingyun Wang, Derong Cao|2021|Chem.Commun.|57|13114|doi:10.1039/D1CC05153A
DOI: 10.5517/ccdc.csd.cc28q2y1
title: CCDC 2106603: Experimental Crystal Structure Determination

description: Related Article: Fang-Fang Duan, Ying Gao, Jun-Jun Liu, Lin Liu, Xiao-Gang Peng, Han-Li Ruan|2021|Org.Chem.Front.|8|7015|doi:10.1039/D1QO01357B
DOI: 10.5517/ccdc.csd.cc28q2z2
title: CCDC 2106604: Experimental Crystal Structure Determination

description: Related Article: Fang-Fang Duan, Ying Gao, Jun-Jun Liu, Lin Liu, Xiao-Gang Peng, Han-Li Ruan|2021|Org.Chem.Front.|8|7015|doi:10.1039/D1QO01357B
DOI: 10.5517/ccdc.csd.cc28q304
title: CCDC 2106605: Experimental Crystal Structure Determination

description: Related Article: Fang-Fang Duan, Ying Gao, Jun-Jun Liu, Lin Liu, Xiao-Gang Peng, Han-Li Ruan|2021|Org.Chem.Front.|8|7015|doi:10.1039/D1QO01357B
DOI: 10.5517/ccdc.csd.cc28q315
title: CCDC 2106606: Experimental Crystal Structure Determination

description: Related Article: Fang-Fang Duan, Ying Gao, Jun-Jun Liu, Lin Liu, Xiao-Gang Peng, Han-Li Ruan|2021|Org.Chem.Front.|8|7015|doi:10.1039/D1QO01357B
DOI: 10.6084/m9.figshare.17125529
title: Scholarly communication in times of crisis: Supplementary data

description: Supplementary data supporting the report, 'Scholarly communication in times of crisis'.
DOI: 10.6084/m9.figshare.17125529.v1
title: Scholarly communication in times of crisis: Supplementary data

description: Supplementary data supporting the report, 'Scholarly communication in times of crisis'.
DOI: 10.5281/zenodo.5765648
title: Training set of microscopy images for Dietler et al. Nature Communications 2020

description: Training set of microscopy images for Dietler et al. Nature Communications 2020
DOI: 10.5281/zenodo.5765647
title: Training set of microscopy images for Dietler et al. Nature Communications 2020

description: Training set of microscopy images for Dietler et al. Nature Communications 2020
DOI: 10.5281/zenodo.5758325
title: Wikidata Dump

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.5758324
title: Wikidata Dump

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.15139/s3/1grslv
title: Testing Dataset

description: For Dataverse testing purposes only.
DOI: 10.6084/m9.figshare.17129282
title: Regional Brain Activities

description: A three dimensional array contained 268 time series for regional activities of each 793 healthy subjects extracted based on Shen's parcellation atlas.
DOI: 10.6084/m9.figshare.17129282.v1
title: Regional Brain Activities

description: A three dimensional array contained 268 time series for regional activities of each 793 healthy subjects extracted based on Shen's parcellation atlas.
DOI: 10.5281/zenodo.5765655
title: Podcast annotation dataset for paper "Identifying Introductions in Podcast Episodes from Automatically Generated Transcripts "

description: Dataset for paper "Identifying Introductions in Podcast Episodes from Automatically Generated Transcripts". Please refer to the paper for details. Compared to the dataset used in the paper, 20 out of the 417 episodes have been removed due to copyright issues. The data file contains the following fields: - "episode_intro_start": the time stamp for episode introduction start (in milliseconds) - "episode_intro_end": the time stamp for episode introduction end (in milliseconds) - "program_intro_start": the time stamp for program introduction start (in milliseconds) - "program_intro_end": the time stamp for program introduction end (in milliseconds) - "program_name": name of the podcast program - "episode_name": name of the podcast episode - "transcription": JSON string containing the transcription, including the timestamps. - "annotator": anonymized annotator ID.
DOI: 10.5281/zenodo.5762441
title: Podcast annotation dataset for paper "Identifying Introductions in Podcast Episodes from Automatically Generated Transcripts "

description: Dataset for paper "Identifying Introductions in Podcast Episodes from Automatically Generated Transcripts". Please refer to the paper for details. Compared to the dataset used in the paper, 20 out of the 417 episodes have been removed due to copyright issues. The data file contains the following fields: - "episode_intro_start": the time stamp for episode introduction start (in milliseconds) - "episode_intro_end": the time stamp for episode introduction end (in milliseconds) - "program_intro_start": the time stamp for program introduction start (in milliseconds) - "program_intro_end": the time stamp for program introduction end (in milliseconds) - "program_name": name of the podcast program - "episode_name": name of the podcast episode - "transcription": JSON string containing the transcription, including the timestamps. - "annotator": anonymized annotator ID.
DOI: 10.6084/m9.figshare.17129312
title: Connectivity Profiles

description: A three dimensional array contained 268 in 268 connectivity matrix of each 793 healthy subjects calculated based on Pearson correlation between regional activations.
DOI: 10.6084/m9.figshare.17129312.v1
title: Connectivity Profiles

description: A three dimensional array contained 268 in 268 connectivity matrix of each 793 healthy subjects calculated based on Pearson correlation between regional activations.
DOI: 10.6084/m9.figshare.17135069
title: Binary Networks (Threshold = 0.1)

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after applying threshold value of 0.1 on functional connections.
DOI: 10.6084/m9.figshare.17135069.v1
title: Binary Networks (Threshold = 0.1)

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after applying threshold value of 0.1 on functional connections.
DOI: 10.6084/m9.figshare.17135108
title: Binary Networks (Threshold = 0.2)

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after applying threshold value of 0.2 on functional connections.
DOI: 10.6084/m9.figshare.17135108.v1
title: Binary Networks (Threshold = 0.2)

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after applying threshold value of 0.2 on functional connections.
DOI: 10.6084/m9.figshare.17135129.v1
title: Binary Networks (Threshold = 0.3)

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after applying threshold value of 0.3 on functional connections.
DOI: 10.6084/m9.figshare.17135129
title: Binary Networks (Threshold = 0.3)

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after applying threshold value of 0.3 on functional connections.
DOI: 10.7910/dvn/x9uwrl
title: Registrations in the AEA RCT Registry (2013-05-15 through 2021-12-07)

description: This dataset contains publicly available data on the American Economic Association's RCT registry downloaded 2021-12-07.
DOI: 10.6084/m9.figshare.17135174
title: Binary Networks (Threshold = 0.4)

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after applying threshold value of 0.4 on functional connections.
DOI: 10.6084/m9.figshare.17135174.v1
title: Binary Networks (Threshold = 0.4)

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after applying threshold value of 0.4 on functional connections.
DOI: 10.6084/m9.figshare.17135210
title: Binary Networks (Threshold = 0.5)

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after applying threshold value of 0.5 on functional connections.
DOI: 10.6084/m9.figshare.17135210.v1
title: Binary Networks (Threshold = 0.5)

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after applying threshold value of 0.5 on functional connections.
DOI: 10.6084/m9.figshare.17135225
title: Signed Networks

description: A three dimensional array contained 268 in 268 signed matrix of each 793 healthy subjects after signing functional connections.
DOI: 10.6084/m9.figshare.17135225.v1
title: Signed Networks

description: A three dimensional array contained 268 in 268 signed matrix of each 793 healthy subjects after signing functional connections.
DOI: 10.6084/m9.figshare.17135882
title: Positive Sub-networks

description: A three dimensional array contained 268 in 268 adjacency matrix of each 793 healthy subjects after considering positive functional connections.
DOI: 10.6084/m9.figshare.17138546.v1
title: Balance Related Features

description: Data frame of balance related features including number of frustrations (FRUS), negative link density (NLD), tendency to make hub of negative subnetwork (TMH), average shortest path length of negative subnetwork (ASPL) and clustering coefficient of negative subnetwork (CC).
DOI: 10.6084/m9.figshare.17138546
title: Balance Related Features

description: Data frame of balance related features including number of frustrations (FRUS), negative link density (NLD), tendency to make hub of negative subnetwork (TMH), average shortest path length of negative subnetwork (ASPL) and clustering coefficient of negative subnetwork (CC).
DOI: 10.6084/m9.figshare.17138549
title: Shen's Regions of Interest

description: Projection of Shen's regions of interest to canonical networks.
DOI: 10.6084/m9.figshare.17138549.v1
title: Shen's Regions of Interest

description: Projection of Shen's regions of interest to canonical networks.
DOI: 10.6084/m9.figshare.17138552
title: Phenotypic Information

description: Phenotypic information of healthy subjects.
DOI: 10.6084/m9.figshare.17138552.v1
title: Phenotypic Information

description: Phenotypic information of healthy subjects.
DOI: 10.25828/vtvj-pv21
title: General Household Survey 2019
DOI: 10.6084/m9.figshare.17131955.v3
title: nasbench-x11-models-v0.5.zip

description: Surrogate models for darts, nasbench-101, and nasbench-nlp search space to output full training curves.
DOI: 10.6084/m9.figshare.17131955.v4
title: nasbench-x11-models-v0.5.zip

description: Surrogate models for darts, nasbench-101, and nasbench-nlp search space to output full training curves.
DOI: 10.6084/m9.figshare.14784579
title: Transposable elements in the genome of the lichen-forming fungus Umbilicaria pustulata, and their distribution in different climate zones along elevation

description: Here we report TEs found in a high quality reference genome of the lichen-forming fungus Umbilicaria pustulata.The fungal symbiont of U. pustulata comprises two climatic ecotypes: Mediterranean and cold-temperate. We implemented a Pool-Seq approach to identify TEs of potential adaptive significance in populations along three replicated elevation gradients.
DOI: 10.6084/m9.figshare.14784579.v1
title: Transposable elements in the genome of the lichen-forming fungus Umbilicaria pustulata, and their distribution in different climate zones along elevation

description: Here we report TEs found in a high quality reference genome of the lichen-forming fungus Umbilicaria pustulata.The fungal symbiont of U. pustulata comprises two climatic ecotypes: Mediterranean and cold-temperate. We implemented a Pool-Seq approach to identify TEs of potential adaptive significance in populations along three replicated elevation gradients.
DOI: 10.5281/zenodo.5731226
title: Rangeland Analysis Platform - vegetation cover v2 1984

description: Rangeland Analysis Platform vegetation cover v2 1984 These data represent rangeland cover estimates determined by Allred et al. (2021)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are estimates of aerial cover for the following rangeland functional groups: Band 1 - annual forb and grass<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forb and grass<br> Band 5 - shrub<br> Band 6 - tree<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Uncertainty values are not included. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Allred, B.W., B.T. Bestelmeyer, C.S. Boyd, C. Brown, K.W. Davies, M.C. Duniway, L.M. Ellsworth, T.A. Erickson, S.D. Fuhlendorf, T.V. Griffiths, V. Jansen, M.O. Jones, J. Karl, A. Knight, J.D. Maestas, J.J. Maynard, S.E. McCord, D.E. Naugle, H.D. Starns, D. Twidwell, and D.R. Uden. 2021. Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty. Methods in ecology and evolution. http://dx.doi.org/10.1111/2041-210x.13564
DOI: 10.5281/zenodo.5731225
title: Rangeland Analysis Platform - vegetation cover v2 1984

description: Rangeland Analysis Platform vegetation cover v2 1984 These data represent rangeland cover estimates determined by Allred et al. (2021)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are estimates of aerial cover for the following rangeland functional groups: Band 1 - annual forb and grass<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forb and grass<br> Band 5 - shrub<br> Band 6 - tree<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Uncertainty values are not included. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Allred, B.W., B.T. Bestelmeyer, C.S. Boyd, C. Brown, K.W. Davies, M.C. Duniway, L.M. Ellsworth, T.A. Erickson, S.D. Fuhlendorf, T.V. Griffiths, V. Jansen, M.O. Jones, J. Karl, A. Knight, J.D. Maestas, J.J. Maynard, S.E. McCord, D.E. Naugle, H.D. Starns, D. Twidwell, and D.R. Uden. 2021. Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty. Methods in ecology and evolution. http://dx.doi.org/10.1111/2041-210x.13564
DOI: 10.5281/zenodo.5731217
title: Rangeland Analysis Platform - vegetation cover v2 1985

description: Rangeland Analysis Platform vegetation cover v2 1985 These data represent rangeland cover estimates determined by Allred et al. (2021)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are estimates of aerial cover for the following rangeland functional groups: Band 1 - annual forb and grass<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forb and grass<br> Band 5 - shrub<br> Band 6 - tree<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Uncertainty values are not included. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Allred, B.W., B.T. Bestelmeyer, C.S. Boyd, C. Brown, K.W. Davies, M.C. Duniway, L.M. Ellsworth, T.A. Erickson, S.D. Fuhlendorf, T.V. Griffiths, V. Jansen, M.O. Jones, J. Karl, A. Knight, J.D. Maestas, J.J. Maynard, S.E. McCord, D.E. Naugle, H.D. Starns, D. Twidwell, and D.R. Uden. 2021. Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty. Methods in ecology and evolution. http://dx.doi.org/10.1111/2041-210x.13564
DOI: 10.5281/zenodo.5731216
title: Rangeland Analysis Platform - vegetation cover v2 1985

description: Rangeland Analysis Platform vegetation cover v2 1985 These data represent rangeland cover estimates determined by Allred et al. (2021)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are estimates of aerial cover for the following rangeland functional groups: Band 1 - annual forb and grass<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forb and grass<br> Band 5 - shrub<br> Band 6 - tree<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Uncertainty values are not included. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Allred, B.W., B.T. Bestelmeyer, C.S. Boyd, C. Brown, K.W. Davies, M.C. Duniway, L.M. Ellsworth, T.A. Erickson, S.D. Fuhlendorf, T.V. Griffiths, V. Jansen, M.O. Jones, J. Karl, A. Knight, J.D. Maestas, J.J. Maynard, S.E. McCord, D.E. Naugle, H.D. Starns, D. Twidwell, and D.R. Uden. 2021. Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty. Methods in ecology and evolution. http://dx.doi.org/10.1111/2041-210x.13564
DOI: 10.5281/zenodo.5731070
title: Rangeland Analysis Platform - vegetation cover v2 1986

description: Rangeland Analysis Platform vegetation cover v2 1986 These data represent rangeland cover estimates determined by Allred et al. (2021)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are estimates of aerial cover for the following rangeland functional groups: Band 1 - annual forb and grass<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forb and grass<br> Band 5 - shrub<br> Band 6 - tree<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Uncertainty values are not included. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Allred, B.W., B.T. Bestelmeyer, C.S. Boyd, C. Brown, K.W. Davies, M.C. Duniway, L.M. Ellsworth, T.A. Erickson, S.D. Fuhlendorf, T.V. Griffiths, V. Jansen, M.O. Jones, J. Karl, A. Knight, J.D. Maestas, J.J. Maynard, S.E. McCord, D.E. Naugle, H.D. Starns, D. Twidwell, and D.R. Uden. 2021. Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty. Methods in ecology and evolution. http://dx.doi.org/10.1111/2041-210x.13564
DOI: 10.5281/zenodo.5731069
title: Rangeland Analysis Platform - vegetation cover v2 1986

description: Rangeland Analysis Platform vegetation cover v2 1986 These data represent rangeland cover estimates determined by Allred et al. (2021)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are estimates of aerial cover for the following rangeland functional groups: Band 1 - annual forb and grass<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forb and grass<br> Band 5 - shrub<br> Band 6 - tree<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Uncertainty values are not included. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Allred, B.W., B.T. Bestelmeyer, C.S. Boyd, C. Brown, K.W. Davies, M.C. Duniway, L.M. Ellsworth, T.A. Erickson, S.D. Fuhlendorf, T.V. Griffiths, V. Jansen, M.O. Jones, J. Karl, A. Knight, J.D. Maestas, J.J. Maynard, S.E. McCord, D.E. Naugle, H.D. Starns, D. Twidwell, and D.R. Uden. 2021. Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty. Methods in ecology and evolution. http://dx.doi.org/10.1111/2041-210x.13564