cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16435221.v2
title: DRL-1

description: numerical raw data for DRL-1 manuscript<br>
DOI: 10.6084/m9.figshare.16435221.v1
title: DRL-1

description: numerical raw data for DRL-1 manuscript<br>
DOI: 10.5281/zenodo.5682826
title: msd-errors - Data for the LLZO figure

description: Results of the diffusion analysis of the LLZO simulations.<br><br>Created using showyourwork from this GitHub repo.
DOI: 10.48372/4e084d1e-b1ac-4649-881f-fe211f77e69b
title: Macrozoobenthos data collected in the Flumendosa river, Sardinia, Italy.

description: The dataset contains taxonomic and body size data of the macroinvertebrates community of the benthic macroinvertebrates community of Flumendosa River (Sardinia, Italy). Data refer to 80 taxa and 14502 individuals.
DOI: 10.5281/zenodo.5675913
title: Test

description: Test Table
DOI: 10.5281/zenodo.5675912
title: Test

description: Test Table
DOI: 10.15468/wamdr4
title: Arisaema brinchangense Y. W. Low, Scherberich & Gusman (Araceae), a new threatened species endemic to the Cameron Highlands (Peninsular Malaysia)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Low, Yee Wen, Scherberich, David, Gusman, Guy (2016): Arisaema brinchangense Y. W. Low, Scherberich & Gusman (Araceae), a new threatened species endemic to the Cameron Highlands (Peninsular Malaysia). Candollea 71 (1): 83-89, DOI: 10.15553/c2016v711a10
DOI: 10.5281/zenodo.5682714
title: EmbeddedNarrationsKleist

description: Annotations of character speech and embedded narrations in Kleists Dramas and Novellas
DOI: 10.5281/zenodo.5682861
title: msd-errors - Data for AgCrSe2 figures

description: Results of the analysis of AgCrSe2 systems by kinisi at a series of temperatures.<br><br>Created using showyourwork from this GitHub repo.
DOI: 10.5522/04/14892822.v1
title: Th17 cell master transcription factor RORC2 regulates HIV-1 gene expression and viral outgrowth

description: Source data files for Figures 1 to 7 and Supporting Information Figures 1 to 10. Methodological details are provided in the original paper and supplementary Methods<br>
DOI: 10.5281/zenodo.5682712
title: SMDemoBioref: Data from the Stan Mayfield Demonstration Biorefinery

description: This dataset includes previously unpublished information collected during the planning and implementation of the University of Florida's Stan Mayfield Demonstration Biorefinery project. <strong>Terms of Use:</strong> These data are provided as is, without any warranties of any kind. A bibliographic citation should be included in the References section of publications and other media to acknowledge the authors of this dataset. Proper citations include the authors, title, publisher, and Digital Object Identifier (DOI) and will allow the products to be discovered and re-used by others.
DOI: 10.15468/4gy9aa
title: Croton aleuritoides P. E. Berry (Euphorbiaceae), a distinctive new tree species from Montagne des Français in northern Madagascar

description: This dataset contains the digitized treatments in Plazi based on the original journal article Berry, Paul E., Ee, Benjamin van, Kainulainen, Kent, Razafindraibe, Hanta (2016): Croton aleuritoides P. E. Berry (Euphorbiaceae), a distinctive new tree species from Montagne des Français in northern Madagascar. Candollea 71 (2): 181-188, DOI: 10.15553/c2016v712a3
DOI: 10.5281/zenodo.4725576
title: English Wikipedia citations with possible SemanticScholar URLs as found by Unpaywall and OAbot

description: Dump of 26025 JSON files each containing one or more URL suggestions for the citations of one English Wikipedia article, of which at least one being a SemanticScholar URL for a green open access copy of an academic work. Compiled between December 2020 and April 2021 with Dissemin's OAbot, using various API sources but mostly Unpaywall data.
description: Citation data is thought to be copyright ineligible. Unpaywall data is CC-0 and embeds various sources. Dissemin data contains data from BASE Search and other sources which are not explicitly CC-0. Individual strings inside citation data may be copyright eligible and subject to the Wikimedia wikis terms of use, being copyright their respective authors, CC-BY-SA 3.0. See the history of each page on en.wikipedia.org at the title contained in the JSON filename (with any "#" replaced by "/").
DOI: 10.5281/zenodo.5683005
title: msd-errors - Data for the LLZO figure

description: Results of the diffusion analysis of the LLZO simulations.<br><br>Created using showyourwork from this GitHub repo.
DOI: 10.5517/ccdc.csd.cc1phbh0
title: CCDC 1563872: Experimental Crystal Structure Determination

description: Related Article: Alan R. Kennedy, Nathan L.C. King, Iain D.H. Oswald, David G. Rollo, Rebecca Spiteri, Aiden Walls|2018|J.Mol.Struct.|1154|196|doi:10.1016/j.molstruc.2017.10.047
DOI: 10.5517/ccdc.csd.cc1phbj1
title: CCDC 1563873: Experimental Crystal Structure Determination

description: Related Article: Alan R. Kennedy, Nathan L.C. King, Iain D.H. Oswald, David G. Rollo, Rebecca Spiteri, Aiden Walls|2018|J.Mol.Struct.|1154|196|doi:10.1016/j.molstruc.2017.10.047
DOI: 10.5517/ccdc.csd.cc1phbk2
title: CCDC 1563874: Experimental Crystal Structure Determination

description: Related Article: Alan R. Kennedy, Nathan L.C. King, Iain D.H. Oswald, David G. Rollo, Rebecca Spiteri, Aiden Walls|2018|J.Mol.Struct.|1154|196|doi:10.1016/j.molstruc.2017.10.047
DOI: 10.5517/ccdc.csd.cc1phbl3
title: CCDC 1563875: Experimental Crystal Structure Determination

description: Related Article: Alan R. Kennedy, Nathan L.C. King, Iain D.H. Oswald, David G. Rollo, Rebecca Spiteri, Aiden Walls|2018|J.Mol.Struct.|1154|196|doi:10.1016/j.molstruc.2017.10.047
DOI: 10.5517/ccdc.csd.cc1phbm4
title: CCDC 1563876: Experimental Crystal Structure Determination

description: Related Article: Alan R. Kennedy, Nathan L.C. King, Iain D.H. Oswald, David G. Rollo, Rebecca Spiteri, Aiden Walls|2018|J.Mol.Struct.|1154|196|doi:10.1016/j.molstruc.2017.10.047
DOI: 10.5517/ccdc.csd.cc1phbn5
title: CCDC 1563877: Experimental Crystal Structure Determination

description: Related Article: Alan R. Kennedy, Nathan L.C. King, Iain D.H. Oswald, David G. Rollo, Rebecca Spiteri, Aiden Walls|2018|J.Mol.Struct.|1154|196|doi:10.1016/j.molstruc.2017.10.047
DOI: 10.5517/ccdc.csd.cc1phbp6
title: CCDC 1563878: Experimental Crystal Structure Determination

description: Related Article: Alan R. Kennedy, Nathan L.C. King, Iain D.H. Oswald, David G. Rollo, Rebecca Spiteri, Aiden Walls|2018|J.Mol.Struct.|1154|196|doi:10.1016/j.molstruc.2017.10.047
DOI: 10.5517/ccdc.csd.cc1zrwp9
title: CCDC 1840212: Experimental Crystal Structure Determination

description: Related Article: R. F. Brissos, L. Korrodi-Gregorio, R. Perez-Tomas, O. Roubeau, P. Gamez|2018|Chem. Squared|2|4|doi:10.28954/2018.csq.11.001
DOI: 10.5517/ccdc.csd.cc1zrwqb
title: CCDC 1840213: Experimental Crystal Structure Determination

description: Related Article: R. F. Brissos, L. Korrodi-Gregorio, R. Perez-Tomas, O. Roubeau, P. Gamez|2018|Chem. Squared|2|4|doi:10.28954/2018.csq.11.001
DOI: 10.5517/ccdc.csd.cc24cthv
title: CCDC 1977567: Experimental Crystal Structure Determination

description: Related Article: Mikhail S. Grigoriev, A.M. Fedoseev, Ph. Moisy|2019|Frumkin Institute of Physical Chemistry and Electrochemistry RAS — 90 years. Collection of papers. M||72|
DOI: 10.5517/ccdc.csd.cc24ctjw
title: CCDC 1977568: Experimental Crystal Structure Determination

description: Related Article: Mikhail S. Grigoriev, A.M. Fedoseev, Ph. Moisy|2019|Frumkin Institute of Physical Chemistry and Electrochemistry RAS — 90 years. Collection of papers. M||72|
DOI: 10.5281/zenodo.5682077
title: Data of the paper "A Technique for the Array Partitioning" submitted to Radio Science

description: Data set of the case A of the paper. The .mat file contains the data, and the .m file uses the data to get the figures of the paper.
DOI: 10.5281/zenodo.5682076
title: Data of the paper "A Technique for the Array Partitioning" submitted to Radio Science

description: Data set of the case A of the paper. The .mat file contains the data, and the .m file uses the data to get the figures of the paper.
DOI: 10.25810/9fca-9471
title: FIRED AUSTRALIA: Tasmania
DOI: 10.25810/atny-2f92
title: FIRED AUSTRALIA: Victoria
DOI: 10.6084/m9.figshare.17001003.v1
title: Knowledge Diversity Model from Paradox of diversity in the collective brain

description: Human societies are collective brains. People within every society have cultural brains—brains that have evolved to selectively seek out adaptive knowledge and socially transmit solutions. Innovations emerge at a population level through the transmission of serendipitous mistakes, incremental improvements and novel recombinations. The rate of innovation through these mechanisms is a function of (1) a society's size and interconnectedness (sociality), which affects the number of models available for learning; (2) fidelity of information transmission, which affects how much information is lost during social learning; and (3) cultural trait diversity, which affects the range of possible solutions available for recombination. In general, and perhaps surprisingly, all three levers can increase and harm innovation by creating challenges around coordination, conformity and communication. Here, we focus on the ‘paradox of diversity’—that cultural trait diversity offers the largest potential for empowering innovation, but also poses difficult challenges at both an organizational and societal level. We introduce ‘cultural evolvability’ as a framework for tackling these challenges, with implications for entrepreneurship, polarization and a nuanced understanding of the effects of diversity. This framework can guide researchers and practitioners in how to reap the benefits of diversity by reducing costs.This article is part of a discussion meeting issue ‘The emergence of collective knowledge and cumulative culture in animals, humans and machines’.
DOI: 10.6084/m9.figshare.17001003
title: Knowledge Diversity Model from Paradox of diversity in the collective brain

description: Human societies are collective brains. People within every society have cultural brains—brains that have evolved to selectively seek out adaptive knowledge and socially transmit solutions. Innovations emerge at a population level through the transmission of serendipitous mistakes, incremental improvements and novel recombinations. The rate of innovation through these mechanisms is a function of (1) a society's size and interconnectedness (sociality), which affects the number of models available for learning; (2) fidelity of information transmission, which affects how much information is lost during social learning; and (3) cultural trait diversity, which affects the range of possible solutions available for recombination. In general, and perhaps surprisingly, all three levers can increase and harm innovation by creating challenges around coordination, conformity and communication. Here, we focus on the ‘paradox of diversity’—that cultural trait diversity offers the largest potential for empowering innovation, but also poses difficult challenges at both an organizational and societal level. We introduce ‘cultural evolvability’ as a framework for tackling these challenges, with implications for entrepreneurship, polarization and a nuanced understanding of the effects of diversity. This framework can guide researchers and practitioners in how to reap the benefits of diversity by reducing costs.This article is part of a discussion meeting issue ‘The emergence of collective knowledge and cumulative culture in animals, humans and machines’.
DOI: 10.25810/hkps-g795
title: FIRED BENIN
DOI: 10.5281/zenodo.5683102
title: msd-errors - Data for AgCrSe2 figures

description: Results of the analysis of AgCrSe2 systems by kinisi at a series of temperatures.<br><br>Created using showyourwork from this GitHub repo.
DOI: 10.15468/trujjj
title: Scrophularia longiflora Benth. and S. nana Stiefelh. (Scrophulariaceae), two distinct species from Iran, confused under the name S. farinosa Boiss.

description: This dataset contains the digitized treatments in Plazi based on the original journal article Ranjbar, Massoud, Rahchamani, Narges, Gautier, Laurent (2016): Scrophularia longiflora Benth. and S. nana Stiefelh. (Scrophulariaceae), two distinct species from Iran, confused under the name S. farinosa Boiss. Candollea 71 (2): 195-203, DOI: 10.15553/c2016v712a5
DOI: 10.5281/zenodo.5682928
title: Discoba protein sequences for protein structure predictions

description: Comprehensive database of Discoba protein sequences, gathered for the purpose of improving protein structure predictions of Discoba species (including <em>Trypanosoma </em>and <em>Leishmania</em>) by AlphaFold and RoseTTAFold. Originally gathered for use with: https://github.com/zephyris/discoba_alphafold
description: Updated to add two new genomes, add a summary statistics files, and transition to a standardised protein sequence scheme in the fasta file: [isolate/species name]_P[protein index]
DOI: 10.25810/xy6k-hy09
title: FIRED BURKINA FASO
DOI: 10.15468/afy6gf
title: On the proper type designation for Camelina microcarpa, a wild relative and possible progenitor of the crop species C. sativa (Brassicaceae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Mosyakin, Sergei L., Brock, Jordan R. (2021): On the proper type designation for Camelina microcarpa, a wild relative and possible progenitor of the crop species C. sativa (Brassicaceae). Candollea 76 (1): 55-63, DOI: 10.15553/c2021v761a4
DOI: 10.25810/gvt2-4j59
title: FIRED DJIBOUTI
DOI: 10.15468/dsgyju
title: Lectotypification of Paramollugo nudicaulis (Molluginaceae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Thulin, Mats (2017): Lectotypification of Paramollugo nudicaulis (Molluginaceae). Candollea 72 (1): 31-34, DOI: 10.15553/c2017v721a4
DOI: 10.15468/5afp3c
title: The anatomy of Odobenocetops (Delphinoidea, Mammalia), the walrus-like dolphin from the Pliocene of Peru and its palaeobiological implications

description: This dataset contains the digitized treatments in Plazi based on the original journal article Muizon, Christian de, Domning, Daryl P. (2002): The anatomy of Odobenocetops (Delphinoidea, Mammalia), the walrus-like dolphin from the Pliocene of Peru and its palaeobiological implications. Zoological Journal of the Linnean Society 134 (4): 423-452, DOI: 10.1046/j.1096-3642.2002.00015.x, URL: https://academic.oup.com/zoolinnean/article-lookup/doi/10.1046/j.1096-3642.2002.00015.x
DOI: 10.25810/hge1-y148
title: FIRED ERITREA
DOI: 10.25810/crdj-vv89
title: FIRED ETHIOPIA
DOI: 10.15468/vnrpqp
title: Amphi-Atlantic distribution of the Mancocumatinae (Cumacea: Bodotriidae), with description of a new genus dwelling in marine lava caves of Tenerife (Canary Islands)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Corbera, Jordi (2002): Amphi-Atlantic distribution of the Mancocumatinae (Cumacea: Bodotriidae), with description of a new genus dwelling in marine lava caves of Tenerife (Canary Islands). Zoological Journal of the Linnean Society 134 (4): 453-461, DOI: 10.1046/j.1096-3642.2002.00016.x, URL: https://academic.oup.com/zoolinnean/article-lookup/doi/10.1046/j.1096-3642.2002.00016.x
DOI: 10.5281/zenodo.4632424
title: Air-sea coupling shapes North American hydroclimate response to ice sheets during the Last Glacial Maximum

description: This data was generated in support of Amaya et al. "Air-sea coupling shapes North American hydroclimate response to ice sheets during the Last Glacial Maximum", published in Earth and Planetary Science Letters. A series of CAM5 simulations (referred to as WM-SST) forced at the lower boundary with the long-term monthly mean SST output from the WM-DOM experiment (e.g., <em>LGM<sub>ICE</sub></em> from DiNezio et al. 2018). Sea ice fraction was prescribed following a repeated seasonal cycle from the CTL-DOM simulation (e.g., <em>PI</em> from DiNezio et al. 2018). Separate experiments were conducted by forcing CAM5 with WM-DOM SSTs (a) globally, (b) in the tropics-only (20˚S-20˚N), (c) in the North Pacific-only (&gt;30˚N), and (d) in the Northern extratropics (&gt;30˚N, all longitudes). Grid points not prescribed with WM-DOM SSTs were set to the CTL SST seasonal cycle. Each simulation was integrated for 40 years. Due to the short decorrelation timescale of the atmosphere, each year of these simulations was treated as a separate ensemble member. All anomalies are relative to a WM-SST control experiment forced with CTL-DOM SSTs globally. Results are shown for the boreal winter (December-February) ensemble average within each experiment.
description: See DiNezio et al. (2018) for a complete model description.
DOI: 10.5281/zenodo.4632423
title: Air-sea coupling shapes North American hydroclimate response to ice sheets during the Last Glacial Maximum

description: This data was generated in support of Amaya et al. "Air-sea coupling shapes North American hydroclimate response to ice sheets during the Last Glacial Maximum", published in Earth and Planetary Science Letters. A series of CAM5 simulations (referred to as WM-SST) forced at the lower boundary with the long-term monthly mean SST output from the WM-DOM experiment (e.g., <em>LGM<sub>ICE</sub></em> from DiNezio et al. 2018). Sea ice fraction was prescribed following a repeated seasonal cycle from the CTL-DOM simulation (e.g., <em>PI</em> from DiNezio et al. 2018). Separate experiments were conducted by forcing CAM5 with WM-DOM SSTs (a) globally, (b) in the tropics-only (20˚S-20˚N), (c) in the North Pacific-only (&gt;30˚N), and (d) in the Northern extratropics (&gt;30˚N, all longitudes). Grid points not prescribed with WM-DOM SSTs were set to the CTL SST seasonal cycle. Each simulation was integrated for 40 years. Due to the short decorrelation timescale of the atmosphere, each year of these simulations was treated as a separate ensemble member. All anomalies are relative to a WM-SST control experiment forced with CTL-DOM SSTs globally. Results are shown for the boreal winter (December-February) ensemble average within each experiment.
description: See DiNezio et al. (2018) for a complete model description.
DOI: 10.5281/zenodo.4632397
title: Glacial changes in tropical climate amplified by the Indian Ocean

description: From DiNezio et al. (2018): "We used CESM1, a model that simulates realistic IPWP climate and is sensitive to changes in the configuration of land masses over the Maritime Continent—a response that is important for simulating glacial climates. CESM1 consists of coupled general circulation models of the atmosphere and ocean, as well as sea ice and land models. Other components of the Earth system, such as the carbon cycle and marine ecosystems, can also be simulated using CESM1; however, we kept them inactive because our focus here is on the climate response to glacial boundary conditions. The climate at the LGM was simulated by prescribing the following boundary conditions: (i) reduced GHG concentrations, (ii) insolation changes due to the orbital configuration at 21 ka, (iii) orography changes due to ice sheets and corresponding roughness length, (iv) surface albedo changes due to ice sheets, and (v) changes in the land-sea distribution and altitude due to lower sea level. A simulation of preindustrial climate was used as control. A series of simulations forced with individual glacial boundary conditions, also known as “single forcing” runs, were used to isolate the climate responses to different glacial drivers. The climate responses and single forcing simulations used to compute them are listed in Table 1. Full details on the implementation of the LGM boundary conditions and the single forcing simulations are available in the Supplementary Materials. The ensemble was augmented by simulations in which the CESM1 atmosphere and land models (CAM5 and CLM4) were coupled to ocean models of varying complexity. These simulations allowed us to explore the importance of ocean-atmosphere coupling in response to ice sheets. First, we replaced the fully dynamical ocean (POP2) with a model of the ocean mixed layer. In this model, the effect of vertical mixing, entrainment, and horizontal currents is prescribed as a seasonally varying heat source or Q-flux. Changes in SSTs computed by this “slab” ocean model can only be influenced by energy exchanges with the atmosphere, such as changes in evaporation or clouds. In the second case, the ocean model consists of climatological SSTs and sea ice extent from the preindustrial control. In this configuration, the air-sea heat fluxes are computed but cannot change the prescribed climatological SST and sea ice extent. Therefore, climate changes simulated in this configuration are due to “uncoupled” atmosphere or land changes. “Thermally coupled” and uncoupled responses were computed from each configuration as in the full-coupled cases by differencing the simulations as specified in Table 1."
description: See DiNezio et al. (2018) Supplementary Materials for a complete model description.
DOI: 10.5281/zenodo.4632396
title: Glacial changes in tropical climate amplified by the Indian Ocean

description: From DiNezio et al. (2018): "We used CESM1, a model that simulates realistic IPWP climate and is sensitive to changes in the configuration of land masses over the Maritime Continent—a response that is important for simulating glacial climates. CESM1 consists of coupled general circulation models of the atmosphere and ocean, as well as sea ice and land models. Other components of the Earth system, such as the carbon cycle and marine ecosystems, can also be simulated using CESM1; however, we kept them inactive because our focus here is on the climate response to glacial boundary conditions. The climate at the LGM was simulated by prescribing the following boundary conditions: (i) reduced GHG concentrations, (ii) insolation changes due to the orbital configuration at 21 ka, (iii) orography changes due to ice sheets and corresponding roughness length, (iv) surface albedo changes due to ice sheets, and (v) changes in the land-sea distribution and altitude due to lower sea level. A simulation of preindustrial climate was used as control. A series of simulations forced with individual glacial boundary conditions, also known as “single forcing” runs, were used to isolate the climate responses to different glacial drivers. The climate responses and single forcing simulations used to compute them are listed in Table 1. Full details on the implementation of the LGM boundary conditions and the single forcing simulations are available in the Supplementary Materials. The ensemble was augmented by simulations in which the CESM1 atmosphere and land models (CAM5 and CLM4) were coupled to ocean models of varying complexity. These simulations allowed us to explore the importance of ocean-atmosphere coupling in response to ice sheets. First, we replaced the fully dynamical ocean (POP2) with a model of the ocean mixed layer. In this model, the effect of vertical mixing, entrainment, and horizontal currents is prescribed as a seasonally varying heat source or Q-flux. Changes in SSTs computed by this “slab” ocean model can only be influenced by energy exchanges with the atmosphere, such as changes in evaporation or clouds. In the second case, the ocean model consists of climatological SSTs and sea ice extent from the preindustrial control. In this configuration, the air-sea heat fluxes are computed but cannot change the prescribed climatological SST and sea ice extent. Therefore, climate changes simulated in this configuration are due to “uncoupled” atmosphere or land changes. “Thermally coupled” and uncoupled responses were computed from each configuration as in the full-coupled cases by differencing the simulations as specified in Table 1."
description: See DiNezio et al. (2018) Supplementary Materials for a complete model description.