cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16895197.v1
title: September 2020 Covid-19 + Vaccines Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in <b>September, 2020</b> from <b>Twitter's COVID-19 Streaming Endpoint </b>via a custom script developed by the <b>Social Media Lab (https://socialmedialab.ca/)</b>.<br>Visit <b>our interactive dashboard at https://stream.covid19misinfo.org</b>/ for a preview and some general stats about this COVID-19 Twitter streaming dataset.<br>For more info about <b>Twitter's COVID-19 Streaming Endpoint</b>, visit <b>https://developer.twitter.com/en/docs/labs/covid19-stream/overview</b><br><b>Note</b>: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895200
title: December 2020 Covid-19 + Vaccines Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in <b>December, 2020</b> from <b>Twitter's COVID-19 Streaming Endpoint </b>via a custom script developed by the <b>Social Media Lab (https://socialmedialab.ca/)</b>.<br>Visit <b>our interactive dashboard at https://stream.covid19misinfo.org</b>/ for a preview and some general stats about this COVID-19 Twitter streaming dataset.<br>For more info about <b>Twitter's COVID-19 Streaming Endpoint</b>, visit <b>https://developer.twitter.com/en/docs/labs/covid19-stream/overview</b><br><b>Note</b>: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895200.v1
title: December 2020 Covid-19 + Vaccines Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in <b>December, 2020</b> from <b>Twitter's COVID-19 Streaming Endpoint </b>via a custom script developed by the <b>Social Media Lab (https://socialmedialab.ca/)</b>.<br>Visit <b>our interactive dashboard at https://stream.covid19misinfo.org</b>/ for a preview and some general stats about this COVID-19 Twitter streaming dataset.<br>For more info about <b>Twitter's COVID-19 Streaming Endpoint</b>, visit <b>https://developer.twitter.com/en/docs/labs/covid19-stream/overview</b><br><b>Note</b>: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.48370/ofd/3ccqlx
title: Puccinia melicae P. Syd. Syd., 1983

description: Fungarium Micromycetes
DOI: 10.25721/6xbb-da56
title: Voisin d'où venait ce grand bruit ?
DOI: 10.5281/zenodo.5606584
title: SemTab 2021 BioTable Dataset

description: This dataset was developed in the context of SemTab 2021: Semantic Web Challenge on Tabular Data to Knowledge Graph Matching. It was used to test the participant systems in the Bio-Track in Round 2. Here you can find not only the files for annotation that were available during the competition but also the ground truths used to evaluate the performance of the system.
DOI: 10.25721/csjh-en23
title: Répondeurs donnez-moi la main
DOI: 10.5281/zenodo.5602814
title: WILIAM Task 7.4

description: This is the official repository of the Task 7.4 of H2020 Locomotion project. Feel free to use our data and comment about our work by referencing the main authors of it. <strong>"create_inputs.txt"</strong> and <strong>"run_simulations.txt"</strong> --&gt; The first Python script creates the input files for EnergyPLAN. The second one runs iteratively EnergyPLAN to generate the outputs of permutations. The<strong> Excel files</strong> saves the information of how data has been prepared to generate the regression models. The <strong>Matlab files</strong> automatically generates the regression models by region of WILIAM (official model of the Locomotion project). The <strong>PowerPoint file</strong> explains the procedure to carry out the runs of permutations on Python/Excel.
DOI: 10.25721/xftv-r451
title: Ban moin un ti bo
DOI: 10.6084/m9.figshare.16546500
title: Supplementary Material for: Dental caries occurrence in Inflammatory Bowel Disease patients. A systematic review and meta-analysis

description: Medicine
DOI: 10.3886/e113497v1-99980
title: Replication data for: Wage Inequality and Firm Growth

description: We discuss firm-level evidence based on UK data showing that within-firm pay inequality--wage differentials between top- and bottom-level jobs--increases with firm size. Moreover, within-firm pay inequality rises as firms grow larger over time. Lastly, using wage data from 15 developed countries, we document a positive association between aggregate wage inequality at the country level and growth by the largest firms in the country. We conclude that part of what may be perceived as a global trend toward more wage inequality may be driven by an increase in the size of the largest firms in the economy.
DOI: 10.25721/n7sr-fx10
title: Ninon
DOI: 10.25721/qjxa-j458
title: Ninon
DOI: 10.15468/fnkh78
title: A new species of the Genus Pelodiscus Fitzinger, 1835 (Testudines: Trionychidae) from Huangshan, Anhui, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Gong, Yan-An, Peng, Li-Fang, Huang, Song, Lin, Yan-Feng, Huang, Ru-Yi, Xu, Yu-Hao, Yang, Dian-Cheng, Nie, Liu-Wang (2021): A new species of the Genus Pelodiscus Fitzinger, 1835 (Testudines: Trionychidae) from Huangshan, Anhui, China. Zootaxa 5060 (1): 137-145, DOI: https://doi.org/10.11646/zootaxa.5060.1.7
DOI: 10.25721/gjzy-jm37
title: Fragment et interruption de biguine
DOI: 10.25721/yvkw-hs07
title: Suite de biguine enchaînée à d'autres airs de biguines
DOI: 10.23728/fmi-b2share.fb5a74c32c0b4e49989334f76b370de2
title: Principal data and analysis code from Riihelä et al (2021): Recent strengthening of snow and ice albedo feedback driven by Antarctic sea ice loss, Nature Geoscience, 2021

description: This entry contains the principal data of the associated publication - the annual global mean snow/ice albedo feedbacks resulting from surface albedo changes over both polar regions (poleward of 50 degrees latitude). Data are available based on CLARA-A2.1 surface albedo data record combined with two radiative kernels; CloudSat-CALIPSO (CC) and CERES-based albedo change kernel (CACK). Upper and lower limits of estimated SIAF uncertainty envelopes are provided in the data file. The entry also provides the principal python codes used in the study. These codes are provided as-is.
DOI: 10.6084/m9.figshare.16818046
title: Disparities among crop species in the evolution of growth rates: the role of distinct origins and domestication histories

description: The "DomesticationRGR" folder consists of four subfolders: The "data" subfolder contains all the input (raw) data used in the analyses for the extensive and intensive experiments. This includes the destructive data used to calibrate mass and area (harvest.xlsx) and the non-destructive data used to fit growth curves (monitoring.xlsx), as well as crop (crop_histories.xlsx) and accession data (acc_origins.xlsx). The "figs" subfolder contains the figures generated by the analyses. The "output" subfolder contains all kinds of intermediate or output files (e.g., processed datasets, etc.). The "scripts" subfolder contains R files documenting the data preparation and statistical analyses (dataprep.R) and the generation of figures (fig1prod.R, fig2prod.R, fig3prod.R, fig4prod.R, fig5prod.R).<br>
DOI: 10.25721/5bdw-4756
title: Air de Lérose, musique gro-ka
DOI: 10.6084/m9.figshare.16818046.v1
title: Disparities among crop species in the evolution of growth rates: the role of distinct origins and domestication histories

description: The "DomesticationRGR" folder consists of four subfolders: The "data" subfolder contains all the input (raw) data used in the analyses for the extensive and intensive experiments. This includes the destructive data used to calibrate mass and area (harvest.xlsx) and the non-destructive data used to fit growth curves (monitoring.xlsx), as well as crop (crop_histories.xlsx) and accession data (acc_origins.xlsx). The "figs" subfolder contains the figures generated by the analyses. The "output" subfolder contains all kinds of intermediate or output files (e.g., processed datasets, etc.). The "scripts" subfolder contains R files documenting the data preparation and statistical analyses (dataprep.R) and the generation of figures (fig1prod.R, fig2prod.R, fig3prod.R, fig4prod.R, fig5prod.R).<br>
DOI: 10.25721/c33c-s396
title: Mazurka
DOI: 10.25721/f84y-pc42
title: Messe de minuit à l'église Saint-Joseph de Vieux-Habitants (programme musical). Gloire à Dieu au plus haut des Cieux (Gloria de la messe à l'ancienne de Cl. Tassin)
DOI: 10.5281/zenodo.5606830
title: Small extracellular vesicles from malignant ascites of patients with advanced ovarian cancer provide insights into the dynamics of the extracellular matrix

description: Small extracellular vesicles isolated from ascites of advanced ovarian cancer patients and assessed with a combination of imaging, proteomic profiling, and protein expression analyses.
DOI: 10.5281/zenodo.5606829
title: Small extracellular vesicles from malignant ascites of patients with advanced ovarian cancer provide insights into the dynamics of the extracellular matrix

description: Small extracellular vesicles isolated from ascites of advanced ovarian cancer patients and assessed with a combination of imaging, proteomic profiling, and protein expression analyses.
DOI: 10.25721/ch76-5245
title: Toi qui était venu chez nous
DOI: 10.6084/m9.figshare.16895227
title: Water quality parameters and hematology profile of Gambusia affinis caught at Brantas River watershed, Indonesia

description: This dataset contains water quality parameter and haematology profile (erythrocyte, leucocyte, micronuclei) of mosquito fish (Gambusia affinis) caught from Brantas River, Indonesia
DOI: 10.6084/m9.figshare.16895242
title: February 2021 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in February, 2021 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895242.v1
title: February 2021 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in February, 2021 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.25721/x1zd-gm69
title: Dans la campagne cette nuit-là alleluia alleluia
DOI: 10.6084/m9.figshare.16895245.v1
title: September 2020 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in September, 2020 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895245
title: September 2020 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in September, 2020 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895260
title: February 2021 Covid-19 + Vaccines Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in <b>February, 2021</b> from <b>Twitter's COVID-19 Streaming Endpoint </b>via a custom script developed by the <b>Social Media Lab (https://socialmedialab.ca/)</b>.<br>Visit <b>our interactive dashboard at https://stream.covid19misinfo.org</b>/ for a preview and some general stats about this COVID-19 Twitter streaming dataset.<br>For more info about <b>Twitter's COVID-19 Streaming Endpoint</b>, visit <b>https://developer.twitter.com/en/docs/labs/covid19-stream/overview</b><br><b>Note</b>: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895272
title: April 2021 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in April, 2021 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895272.v1
title: April 2021 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in April, 2021 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895281
title: Supplementary Material for: Pyoderma Gangrenosum and Interleukin Inhibitors: A Semi-Systematic Review

description: <b><i>Background:</i></b> Pyoderma gangrenosum (PG) is a rare ulcerating skin disease associated with multiple comorbidities and increased mortality. In recent decades, newer biologics such as interleukin inhibitors have been used to treat PG; however, the literature is scarce, consisting predominantly of case reports and caseseries. The aim of our review was to evaluate the effectiveness and safety of interleukin inhibitors for the treatment of PG in adults. <b><i>Summary:</i></b> A literature search was conducted using search terms related to PG and interleukin inhibitors in databases such as PubMed, Embase, Scopus, Web of Science, and Cochrane Library. The study eligibility criteria included patients diagnosed with PG, over the age of 18, and treated with an interleukin inhibitor. Our study included 60 papers describing 81 patients fulfilling the eligibility criteria. The treatment with interleukin inhibitors resulted in 70% (95% CI 59–80%) response and 57% (95% CI 45–68%) complete response rates, and few (4%) mild adverse events, hence supporting the off-label use for the treatment of recalcitrant PG in adults. The response and complete response rates were 59% (17/29) and 38% (11/29) for anakinra, 64% (7/11) and 55% (6/11) for canakinumab, and 79% (27/34) and 71% (24/34) for ustekinumab, respectively. Limitations include publication bias that might have overestimated the efficacy as successful cases responding to treatment are more likely to be reported than nonresponding cases. Additionally, the heterogeneity of the treatment groups does not allow conclusions of superiority or inferiority of the different interleukin inhibitors to be drawn. Further studies are needed to investigate the efficacy of the different interleukin inhibitors and to investigate the importance of underlying disease for treatment response.
DOI: 10.6084/m9.figshare.16895284
title: August 2020 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in August, 2020 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895284.v1
title: August 2020 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in August, 2020 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895287.v1
title: March 2021 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in March, 2021 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16895287
title: March 2021 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in March, 2021 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.16530792
title: Alignments gene by gene

description: Alignments (by gene) used in the paper "<b>Molecular phylogeny of <i>Allodia </i>(Diptera: Mycetophilidae) constructed using genome skimming"</b>
DOI: 10.6084/m9.figshare.16895299.v1
title: December 2020 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in December, 2020 from Twitter's COVID-19 Streaming Endpoint via a custom script developed by the Social Media Lab (https://socialmedialab.ca/). Visit our interactive dashboard at https://stream.covid19misinfo.org/ for a preview and some general stats about this COVID-19 Twitter streaming dataset. For more info about Twitter's COVID-19 Streaming Endpoint, visit https://developer.twitter.com/en/docs/labs/covid19-stream/overview * Note: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).