cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4621403
title: Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection

description: Full-Text PDF<br> Title: Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection<br> Authors: Jan Philip Wahle, Terry Ruas, Norman Meuschke, and Bela Gipp<br> Contact email: wahle@uni-wuppertal.de; ruas@uni-wuppertal.de<br> Venue: JCDL<br> Year: 2021<br> ================================================================<br> <strong>Dataset Description:</strong> <em><strong>Training:</strong></em><br> 1,474,230 aligned paragraphs (98,282 original, 1,375,948 paraphrased with 3 models and 5 hyperparameter configurations each 98,282) extracted from 4,012 (English) Wikipedia articles. <em><strong>Testing:</strong></em><br> BERT-large (cased): <br> arXiv - Original - 20,966; Paraphrased - 20,966; <br> Theses - Original - 5,226; Paraphrased - 5,226;<br> Wikipedia - Original - 39,241; Paraphrased - 39,241;<br> <br> RoBERTa-large (cased): <br> arXiv - Original - 20,966; Paraphrased - 20,966; <br> Theses - Original - 5,226; Paraphrased - 5,226;<br> Wikipedia - Original - 39,241; Paraphrased - 39,241; Longformer-large (uncased): <br> arXiv - Original - 20,966; Paraphrased - 20,966; <br> Theses - Original - 5,226; Paraphrased - 5,226;<br> Wikipedia - Original - 39,241; Paraphrased - 39,241; ================================================================ Dataset Structure: <strong>[og]</strong> folder: original. The original documents are split by the data source with the following folders: <strong>[arxiv]</strong> <strong>[thesis]</strong> <strong>[wikipedia]</strong> <strong>[wikipedia_train]</strong> <strong>[`model_name`_mlm_prob_`probability`] (e.g., bert-large-cased_mlm_prob_0.15): </strong>contains all paraphrased examples using the model with name `model_name` and Masked Language Modeling probability `probability`.<br> Each paraphrase model/probability folder contains the corresponding paraphrased documents according to<strong> [of]</strong>: <strong>[arxiv]</strong> <strong>[thesis]</strong> <strong>[wikipedia]</strong> <strong>[wikipedia_train]</strong> hparams.yml hparams.yml contains the hyperparameters to reconstruct the dataset using the official repository. ================================================================ Files:<br> On the lowest folder level, each `.txt` file contains exactly one paragraph. The filename contains either "ORIG" for original, or "SPUN" for paraphrased. ================================================================ Code:<br> To avoid misuse of the code for constructing machine-paraphrased plagiarism, you must consent to our Terms and Conditions and send the signed version via mail to one of the contact addresses above to obtain access to our repository (see TermsAndConditions.pdf).
DOI: 10.20372/aau_rdr/ofrkzw/vdmwyi
title: Atnafu AAU SPSS 2022.tab

description: :unav
DOI: 10.20372/aau_rdr/ofrkzw
title: Perceptions of couples towards infertility

description: Perceptions of couples towards infertility and its effect on Assisted Reproductive Technology’s (ARTs) use: The case of St. Paul Hospital fertility center, Addis Ababa
DOI: 10.15151/esrf-es-922456711
title: Structural Biology of Macromolecules and Macromolecular complexes from India

description: Structural biology research groups located in India constitute the INDIA-BAG and will utilize MX & SAXS to study different biological macromolecules. The non-proprietary agreement signed between ESRF and the Department of Biotechnology (DBT) enables studies that provide fundamental mechanistic insight regarding different biological processes. A brief description of over 50 research groups is provided in the global summary and a summary of their research contributions involving data collected at ESRF is provided in the 2 year BAG report. The ESRF-India partnership is supported by a single grant provided to the RCB by the DBT. Please note that a report listing no. of shifts utilized, details of users and the research output from these visits has to be sent to the DBT to obtain release of funds to pay ESRF membership dues. Consequently, all the structural biologists from India are grouped in a single BAG to enable monitoring of progress to collect the required statistics.
DOI: 10.5281/zenodo.7296222
title: Mastodon project containing the cell tracks of a developing Tribolium Castaneum embryo.

description: Mastodon project containing the cell tracks of a developing <em>Tribolium Castaneum </em>embryo. To open it in Mastodon, download both the <em>.mastodon </em>and the <em>.xml </em>files and put them in the same folder. The image data is stored on a BigDataServer in the Institut Pasteur, Paris, provided by the Image Analysis Hub. When you open this <em>.mastodon </em>file with Mastodon, it will stream the image from the server without you having to download it. The mastodon file contains just the tracks and the <em>.xml </em>file contins the address of the server from where the image data will be streamed. Check the Mastodon scientific software for information on how to open and use this file for scientific purposes. The image data is the 'TRIF' training video 02 from the CellTrackingChallenge.net, with authorization. The original dataset provider is Dr. A. Jain. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. Microscope: Zeiss LightSheet LZ.1 Objective lens: Plan-Apochromat 20x/1.0 (water) Voxel size (microns): 0.38 x 0.38 x 0.38 Time step (min): 1.5
DOI: 10.5281/zenodo.7296162
title: Mastodon project containing the cell tracks of a developing Tribolium Castaneum embryo.

description: Mastodon project containing the cell tracks of a developing <em>Tribolium Castaneum </em>embryo. To open it in Mastodon, download both the <em>.mastodon </em>and the <em>.xml </em>files and put them in the same folder. The image data is stored on a BigDataServer in the Institut Pasteur, Paris, provided by the Image Analysis Hub. When you open this <em>.mastodon </em>file with Mastodon, it will stream the image from the server without you having to download it. The mastodon file contains just the tracks and the <em>.xml </em>file contins the address of the server from where the image data will be streamed. Check the Mastodon scientific software for information on how to open and use this file for scientific purposes. The image data is the 'TRIF' training video 02 from the CellTrackingChallenge.net, with authorization. The original dataset provider is Dr. A. Jain. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. Microscope: Zeiss LightSheet LZ.1 Objective lens: Plan-Apochromat 20x/1.0 (water) Voxel size (microns): 0.38 x 0.38 x 0.38 Time step (min): 1.5
DOI: 10.5281/zenodo.7295455
title: Siegel et al 2022 data and code

description: Data and code for the analysis in the paper "Accounting for snowpack and time-varying lags in statistical models of stream temperature" Journal of Hydrology X, Volume 17, 1 December 2022, 100136
DOI: 10.5281/zenodo.7295454
title: Siegel et al 2022 data and code

description: Data and code for the analysis in the paper "Accounting for snowpack and time-varying lags in statistical models of stream temperature" Journal of Hydrology X, Volume 17, 1 December 2022, 100136
DOI: 10.34740/kaggle/dsv/4457812
title: AAC: climbing accidents and major new climbs
DOI: 10.5517/ccdc.csd.cc2c3b72
title: CCDC 2177943: Experimental Crystal Structure Determination

description: Related Article: Benita Barton, Mino R. Caira, Ulrich Senekal, Eric C Hosten|2022|Cryst.Growth Des.|22|6818|doi:10.1021/acs.cgd.2c00990
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.cc2c3b83
title: CCDC 2177944: Experimental Crystal Structure Determination

description: Related Article: Benita Barton, Mino R. Caira, Ulrich Senekal, Eric C Hosten|2022|Cryst.Growth Des.|22|6818|doi:10.1021/acs.cgd.2c00990
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.cc2bttpp
title: CCDC 2169773: Experimental Crystal Structure Determination

description: Related Article: Wanli Zhou, Yuecen Guan, Yanping Zheng, Xiao Chen, Jinyang Li, Xuekun Liu, Jun Peng|2022|Cryst.Growth Des.|22|6588|doi:10.1021/acs.cgd.2c00805
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.cc2d2khk
title: CCDC 2206998: Experimental Crystal Structure Determination

description: Related Article: Laura Tadiello, Hans-Joachim Drexler, Torsten Beweries|2022|Organometallics|41|2833|doi:10.1021/acs.organomet.2c00301
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.cc2d2mmr
title: CCDC 2207064: Experimental Crystal Structure Determination

description: Related Article: Jan Paciorek, Denis Höfler, Kevin Rafael Sokol, Klaus Wurst, Thomas Magauer|2022|J.Am.Chem.Soc.|144|19704|doi:10.1021/jacs.2c10010
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.cc2d2mns
title: CCDC 2207065: Experimental Crystal Structure Determination

description: Related Article: Jan Paciorek, Denis Höfler, Kevin Rafael Sokol, Klaus Wurst, Thomas Magauer|2022|J.Am.Chem.Soc.|144|19704|doi:10.1021/jacs.2c10010
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.cc2d2mpt
title: CCDC 2207066: Experimental Crystal Structure Determination

description: Related Article: Jan Paciorek, Denis Höfler, Kevin Rafael Sokol, Klaus Wurst, Thomas Magauer|2022|J.Am.Chem.Soc.|144|19704|doi:10.1021/jacs.2c10010
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.cc2c1yjx
title: CCDC 2176619: Experimental Crystal Structure Determination

description: Related Article: Benita Barton, Mino R. Caira, Ulrich Senekal, Eric C Hosten|2022|Cryst.Growth Des.|22|6818|doi:10.1021/acs.cgd.2c00990
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.cc2d5dll
title: CCDC 2209729: Experimental Crystal Structure Determination

description: Related Article: Yan He, Qimeng Liu, Zihe Du, Yanhua Xu, Lingyu Cao, Xinying Zhang, Xuesen Fan|2022|J.Org.Chem.|87|14840|doi:10.1021/acs.joc.2c01290
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.cc2bspxr
title: CCDC 2168695: Experimental Crystal Structure Determination

description: Related Article: Sumera Zaib, Aliya Ibrar, Imtiaz Khan, Rosa M. Gomila, Muhammad Umair Tariq, Jim Simpson, Christopher John McAdam, Hamad Alrbyawi, Rami Adel Pashameah, Eman Alzahrani, Abd-ElAziem Farouk, Antonio Frontera|2022|J.Mol.Struct.|1273|134387|doi:10.1016/j.molstruc.2022.134387
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: 10.5281/zenodo.7108316
title: Dimensionality reduction of local structure in glassy binary mixtures

description: This dataset is associated with "<em>Dimensionality reduction of local structure in glassy binary mixtures</em>", by D. Coslovich, R. L. Jack, J. Paret. It includes data and workflow to allow for the replication of the analysis and figures of the manuscript. To reproduce the workflow and the figures, download and extract the package sprouts.tar.gz, then execute <pre><code class="language-bash">./make all</code></pre> This will create the figures under plots/paper and recompile project.pdf. If the workflow fails because of missing dependencies, read the project.pdf file below and check the requirements, or download the docker image sprouts-docker.tar.gz, load the image and execute the same command within the container. <em>Make sure you have at least 20 Gb of free space on your disk if you use the package, and 22 Gb if you use the docker image.</em> To speed up the execution of the workflow, download the data cache (cache.tar) and extract it at the root of the project folder. See project.pdf below for full details about the workflow. <strong>Changelog</strong>: 1.0.2: use more portable she-bang in scripts 1.0.1: fix typos, remove some dead code 1.0.0: initial submission
DOI: 10.5281/zenodo.7278183
title: Dimensionality reduction of local structure in glassy binary mixtures

description: This dataset is associated with "<em>Dimensionality reduction of local structure in glassy binary mixtures</em>", by D. Coslovich, R. L. Jack, J. Paret. It includes data and workflow to allow for the replication of the analysis and figures of the manuscript. To reproduce the workflow and the figures, download and extract the package sprouts.tar.gz, then execute <pre><code class="language-bash">./make all</code></pre> This will create the figures under plots/paper and recompile project.pdf. If the workflow fails because of missing dependencies, read the project.pdf file below and check the requirements, or download the docker image sprouts-docker.tar.gz, load the image and execute the same command within the container. <em>Make sure you have at least 20 Gb of free space on your disk if you use the package, and 22 Gb if you use the docker image.</em> To speed up the execution of the workflow, download the data cache (cache.tar) and extract it at the root of the project folder. See project.pdf below for full details about the workflow. <strong>Changelog</strong>: 1.0.1: fix typos, remove some dead code 1.0.0: initial submission
DOI: 10.5281/zenodo.7296251
title: Dimensionality reduction of local structure in glassy binary mixtures

description: This dataset is associated with "<em>Dimensionality reduction of local structure in glassy binary mixtures</em>", by D. Coslovich, R. L. Jack, J. Paret. It includes data and workflow to allow for the replication of the analysis and figures of the manuscript. To reproduce the workflow and the figures, download and extract the package sprouts.tar.gz, then execute <pre><code class="language-bash">./make all</code></pre> This will create the figures under plots/paper and recompile project.pdf. If the workflow fails because of missing dependencies, read the project.pdf file below and check the requirements, or download the docker image sprouts-docker.tar.gz, load the image and execute the same command within the container. <em>Make sure you have at least 20 Gb of free space on your disk if you use the package, and 22 Gb if you use the docker image.</em> To speed up the execution of the workflow, download the data cache (cache.tar) and extract it at the root of the project folder. See project.pdf below for full details about the workflow. <strong>Changelog</strong>: 1.0.2: use more portable she-bang in scripts 1.0.1: fix typos, remove some dead code 1.0.0: initial submission
DOI: 10.6084/m9.figshare.21507615
title: Ancient and nonuniform loss of olfactory receptor expression renders the shark nose a de facto vomeronasal organ

description: - Concatenaed_alignment.faa = Concatenated gene alignment of 1068 BUSCO genes retrieved in 12 Chondrichthyes. <br> - partitions.txt = Position of each partition (each gene) in the concatenated alignment <br> - partitions.txt.best_scheme.nex = Best model found by ModelFinder for each partition of the concatenaed alignment. - DATE_FILE.txt = Calibration points used, found in TimeTree <br> - partitions.txt.best_scheme.nex.timetree.nex = Species tree in nexus format <br> - README.txt = IQ-TREE2 command to reproduce the species tree.
DOI: 10.6084/m9.figshare.21507615.v1
title: Ancient and nonuniform loss of olfactory receptor expression renders the shark nose a de facto vomeronasal organ

description: - Concatenaed_alignment.faa = Concatenated gene alignment of 1068 BUSCO genes retrieved in 12 Chondrichthyes. <br> - partitions.txt = Position of each partition (each gene) in the concatenated alignment <br> - partitions.txt.best_scheme.nex = Best model found by ModelFinder for each partition of the concatenaed alignment. - DATE_FILE.txt = Calibration points used, found in TimeTree <br> - partitions.txt.best_scheme.nex.timetree.nex = Species tree in nexus format <br> - README.txt = IQ-TREE2 command to reproduce the species tree.
DOI: 10.5281/zenodo.5732799
title: Prediction of metabolites associated with somatic mutations in cancers

description: GEMs_AML: 16 acute myeloid leukemia (AML) patient-specific genome-scale metabolic models (GEMs) reconstructed using their corresponding RNA-seq data and Recon 2M.2 GEMs_PCAWG: 943 cancer patient-specific GEMs for 24 different cancer types reconstructed using the Pan-Cancer Analysis of Whole Genomes (PCAWG) RNA-seq data and generic human GEM 'Recon 2M.2' GEMs_RCC: 20 renal cell carcinoma (RCC) patient-specific GEMs reconstructed using their corresponding RNA-seq data and Recon 2M.2 GEMs_TCGA_LAML: 113 AML patient-specific GEMs reconstructed using The Cancer Genome Atlas (TCGA) LAML RNA-seq data and Recon 2M.2
description: This study was supported by the Project of Promoting Inclusive Growth through Artificial Intelligence and Blockchain Technology and Diffusion of Precision Medicine (1711125351) funded by the Ministry of Science and ICT through KAIST's Korea Policy Center for the Fourth Industrial Revolution. This work was also supported by the KAIST Cross-Generation Collaborative Lab project of the Ministry of Science and ICT through the National Research Foundation of Korea, and by Kwon Oh-Hyun Assistant Professor fund of the KAIST Development Foundation.
DOI: 10.5281/zenodo.5732800
title: Prediction of metabolites associated with somatic mutations in cancers

description: GEMs_PCAWG: 943 cancer patient-specific genome-scale metabolic models (GEMs) for 24 different cancer types reconstructed using the Pan-Cancer Analysis of Whole Genomes (PCAWG) RNA-seq data and generic human GEM 'Recon 2M.2' GEMs_AML: 16 acute myeloid leukemia (AML) patient-specific GEMs using their corresponding RNA-seq data and Recon 2M.2
DOI: 10.5281/zenodo.7296304
title: Prediction of metabolites associated with somatic mutations in cancers

description: GEMs_AML: 16 acute myeloid leukemia (AML) patient-specific genome-scale metabolic models (GEMs) reconstructed using their corresponding RNA-seq data and Recon 2M.2 GEMs_PCAWG: 943 cancer patient-specific GEMs for 24 different cancer types reconstructed using the Pan-Cancer Analysis of Whole Genomes (PCAWG) RNA-seq data and generic human GEM 'Recon 2M.2' GEMs_RCC: 20 renal cell carcinoma (RCC) patient-specific GEMs reconstructed using their corresponding RNA-seq data and Recon 2M.2 GEMs_TCGA_LAML: 113 AML patient-specific GEMs reconstructed using The Cancer Genome Atlas (TCGA) LAML RNA-seq data and Recon 2M.2
description: This study was supported by the Project of Promoting Inclusive Growth through Artificial Intelligence and Blockchain Technology and Diffusion of Precision Medicine (1711125351) funded by the Ministry of Science and ICT through KAIST's Korea Policy Center for the Fourth Industrial Revolution. This work was also supported by the KAIST Cross-Generation Collaborative Lab project of the Ministry of Science and ICT through the National Research Foundation of Korea, and by Kwon Oh-Hyun Assistant Professor fund of the KAIST Development Foundation.
DOI: 10.5519/qd.ysi2mrw7
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1001 records)
DOI: 10.5281/zenodo.7290350
title: H_clinopyroxene_equilibration

description: This supplementary material contains all MATLAB© programs that have been written to model non-isothermal diffusion of hydrogen in clinopyroxene along geotherms (P-T-fO2 path). Note: This is a sequence of codes that should be used in the order shown below. The first code produces an .xlsx (EXCEL file) output file that is then read from the next code and so on. The last code in this sequence is the non-isothermal diffusion model that uses all the information contained in the single .xlsx file to calculate the diffusion process. Geotherm.m: This code was used to calculate P-T paths. COH_geotherm.m: This code was used to calculate fluid composition along the model P-T paths using following .mat files that contain fugacity coefficients: fugacity_coefficient_CH4.mat fugacity_coefficient_CO.mat fugacity_coefficient_CO2.mat fugacity_coefficient_H2.mat fugacity_coefficient_H2O.mat fugacity_coefficient_P_kbar.mat fugacity_coefficient_T_C.mat yCH4_extrapolated.mat yCO_extrapolated.mat yCO2_extrapolated.mat yH2_extrapolated.mat yH2O_extrapolated.mat interp2D.m H2Ocpx_sol.m: This code calculates the solubility concentration along the P-T path as a function of water fugacity, temperature, and pressure. non_isothermal_diffusion.m: This code is the actual non-isothermal model that reads the input data from the .xlsx file reeq_coolingrate.m: This code can be used to calculate a re-equilibration map.