cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5580016
title: MercadoLibreData

description: El dataset contiene datos de un conjunto de productos que se ofertan en diferentes países. Estos están relacionados con el precio de venta con la finalidad de determinar el índice de carestía, la demanda u oferta actual, el costo de producción o fabricación según el sitio en el que se distribuye el bien. Adicional a esto existe información relacionada con las características básicas de los productos, permitiendo conocer especificaciones que son exclusivas en ciertos lugares. La unidad monetaria inicialmente está reflejada según la moneda local, pero en el script se realiza un cálculo adicional para establecer un valor referencial en dólares que permite diferenciar los precios en un rango único de valores. La información obtenida requiere un proceso de clasificación, procesado y limpieza con la finalidad de encontrar inconsistencias que disminuyen la calidad de la data. Como ejemplo se puede mencionar que en la columna precio existen valores nulos, la unidad monetaria no contiene valor en algunos casos o se necesita transformarla, la columna descripción puede contener información poco relevante para el caso de estudio. El dataset inicialmente cuenta con 5 columnas distribuidas en 91 filas, la información corresponde a productos tecnológicos y su formato de extracción es csv. <strong># Estructura de los datos</strong> | Columna | Descripción | | ------------ | ----------- | | product | Nombre del producto buscado | | country | País del subsitio de Mercado libre buscado | | url | URL del item encontrado | | precio | Precio junto con su moneda | | item | Nombre completo del item encontrado |
DOI: 10.5281/zenodo.5580015
title: MercadoLibreData

description: El dataset contiene datos de un conjunto de productos que se ofertan en diferentes países. Estos están relacionados con el precio de venta con la finalidad de determinar el índice de carestía, la demanda u oferta actual, el costo de producción o fabricación según el sitio en el que se distribuye el bien. Adicional a esto existe información relacionada con las características básicas de los productos, permitiendo conocer especificaciones que son exclusivas en ciertos lugares. La unidad monetaria inicialmente está reflejada según la moneda local, pero en el script se realiza un cálculo adicional para establecer un valor referencial en dólares que permite diferenciar los precios en un rango único de valores. La información obtenida requiere un proceso de clasificación, procesado y limpieza con la finalidad de encontrar inconsistencias que disminuyen la calidad de la data. Como ejemplo se puede mencionar que en la columna precio existen valores nulos, la unidad monetaria no contiene valor en algunos casos o se necesita transformarla, la columna descripción puede contener información poco relevante para el caso de estudio. El dataset inicialmente cuenta con 5 columnas distribuidas en 91 filas, la información corresponde a productos tecnológicos y su formato de extracción es csv. <strong># Estructura de los datos</strong> | Columna | Descripción | | ------------ | ----------- | | product | Nombre del producto buscado | | country | País del subsitio de Mercado libre buscado | | url | URL del item encontrado | | precio | Precio junto con su moneda | | item | Nombre completo del item encontrado |
DOI: 10.6084/m9.figshare.16864627
title: Supplementary Material – Pollen morphology of selected species of Anacardiaceae and its taxonomic significance

description: <b>Table S1 – </b>Pollen morphometric characteristics and measurements (μm) for species of Anacardiaceae. <b>Table S2 – </b>Morphological characters of the pollen grains of the species of Anacardiaceae. <br>see Original Paper: http://dx.doi.org/10.1590/2175-7860202172115
DOI: 10.6084/m9.figshare.16864627.v1
title: Supplementary Material – Pollen morphology of selected species of Anacardiaceae and its taxonomic significance

description: <b>Table S1 – </b>Pollen morphometric characteristics and measurements (μm) for species of Anacardiaceae. <b>Table S2 – </b>Morphological characters of the pollen grains of the species of Anacardiaceae. <br>see Original Paper: http://dx.doi.org/10.1590/2175-7860202172115
DOI: 10.6084/m9.figshare.16862959
title: Mscs sequencing data

description: the RNA sequencing data of two pig Mscs
DOI: 10.6084/m9.figshare.16862959.v1
title: Mscs sequencing data

description: the RNA sequencing data of two pig Mscs
DOI: 10.6084/m9.figshare.16864660
title: SANER 2022 (On the Assessment of Continuous Detection of Code Smells: An Empirical Study)

description: On the Assessment of Continuous Detection of Code Smells: An Empirical Study
DOI: 10.6084/m9.figshare.16864660.v1
title: SANER 2022 (On the Assessment of Continuous Detection of Code Smells: An Empirical Study)

description: On the Assessment of Continuous Detection of Code Smells: An Empirical Study
DOI: 10.5281/zenodo.4421969
title: Status quo in data availability and predictive models of nano-mixture toxicity

description: Supplementary materials for manuscript: Status quo in data availability and predictive models of nano-mixture toxicity. This table contains the list of 183 curated literature used in this study.
description: Link to publication: https://doi.org/10.3390/nano11010124
description: {"references": ["https://doi.org/10.3390/nano11010124"]}
DOI: 10.5281/zenodo.4339738
title: Status quo in data availability and predictive models of nano-mixture toxicity

description: Supplementary materials for manuscript: Status quo in data availability and predictive models of nano-mixture toxicity. This table contains the list of 183 curated literature used in this study.
description: Link to publication: https://doi.org/10.3390/nano11010124
description: {"references": ["https://doi.org/10.3390/nano11010124"]}
DOI: 10.25540/z5s2-s1v=
title: Trust and Trade-Offs in Sharing Data for Precision Medicine: A National Survey of Singapore

description: This dataset contains data from a stratified random sample of 1000 respondents of Singapore citizens and permanent residents. The dataset was used in the adaptive choice-based conjoint (ACBC) analysis for our household survey conducted in 2021 that with the aim of assessing Singaporean public preferences and priorities for sharing health-related data for Precision Medicine (PM). The 4 attributes used in the ACBC analysis were uses, users of health data, data sensitivity and consent for sharing data. Please refer to the related publication via the link: https://doi.org/10.3390/jpm11090921 .
description: The dataset is presented in an Excel workbook consisting of 3 tabs: - - “Variable description” consists of the definitions of variables and variable levels listed in the tab “Database”. - - “Database” consists of the complete set of survey data from 1,000 respondents. - - “Attribute” has the list of attributes and their respective attribute levels that were used in the ACBC analysis.
DOI: 10.5281/zenodo.5574799
title: Dataset of CCFs and Vs values

description: The data stored here is the results of cross-correlation functions and Vs profiles in the paper of ‘Extraction of P and Scholte waves from ambient seafloor noise observed by distributed acoustic sensing’, by Tonegawa et al. The format is described in README file.
DOI: 10.6084/m9.figshare.16864744
title: Additional file 2 of Bayesian additional evidence for decision making under small sample uncertainty

description: Additional file 2. (R 2 kb)
DOI: 10.6084/m9.figshare.16864744.v1
title: Additional file 2 of Bayesian additional evidence for decision making under small sample uncertainty

description: Additional file 2. (R 2 kb)
DOI: 10.6084/m9.figshare.16864781
title: Additional file 1 of Application of the 3′ mRNA-Seq using unique molecular identifiers in highly degraded RNA derived from formalin-fixed, paraffin-embedded tissue

description: Additional file 1: Supplemental Data S1. Sample information and QC metrics of the QuantSeq 3′ mRNA-Seq with UMI.
DOI: 10.6084/m9.figshare.16864781.v1
title: Additional file 1 of Application of the 3′ mRNA-Seq using unique molecular identifiers in highly degraded RNA derived from formalin-fixed, paraffin-embedded tissue

description: Additional file 1: Supplemental Data S1. Sample information and QC metrics of the QuantSeq 3′ mRNA-Seq with UMI.
DOI: 10.6084/m9.figshare.16864831
title: Additional file 4 of Mediation analysis methods used in observational research: a scoping review and recommendations

description: Additional file 4: Supplementary appendix 4. Dataset with extracted data.
DOI: 10.6084/m9.figshare.16864831.v1
title: Additional file 4 of Mediation analysis methods used in observational research: a scoping review and recommendations

description: Additional file 4: Supplementary appendix 4. Dataset with extracted data.
DOI: 10.6084/m9.figshare.16864870
title: Additional file 6 of MYCN and MAX alterations in Wilms tumor and identification of novel N-MYC interaction partners as biomarker candidates

description: Additional file 6: Table S1. Summary of mutation screening results and clinical data. Table S2. Overlap of WT patients with the MYCN P44L and DROSHA E1147K mutations. p = p-value (two-tailed Fisher's exact test). Table S3. Proteins identified in N-MYC protein complexes. Table S4. Cellular component clustering for N-MYC interacting proteins identified in MS. Table S5. Statistics of MYCN/YEATS2/PEG10 expression in Wilms tumor. Table S6. Oligonucleotides for MYCN and MAX mutation screening. Table S7. Oligonucleotides for gene cloning. Table S8. Doxycycline concentrations for MYCN/MAX induction. Table S9. Oligonucleotides for real-time PCR. Table S10. Antibodies for Western Blot.
DOI: 10.6084/m9.figshare.16864870.v1
title: Additional file 6 of MYCN and MAX alterations in Wilms tumor and identification of novel N-MYC interaction partners as biomarker candidates

description: Additional file 6: Table S1. Summary of mutation screening results and clinical data. Table S2. Overlap of WT patients with the MYCN P44L and DROSHA E1147K mutations. p = p-value (two-tailed Fisher's exact test). Table S3. Proteins identified in N-MYC protein complexes. Table S4. Cellular component clustering for N-MYC interacting proteins identified in MS. Table S5. Statistics of MYCN/YEATS2/PEG10 expression in Wilms tumor. Table S6. Oligonucleotides for MYCN and MAX mutation screening. Table S7. Oligonucleotides for gene cloning. Table S8. Doxycycline concentrations for MYCN/MAX induction. Table S9. Oligonucleotides for real-time PCR. Table S10. Antibodies for Western Blot.
DOI: 10.6084/m9.figshare.16864897
title: Additional file 1 of Prediction of pandemic risk for animal-origin coronavirus using a deep learning method

description: Additional file 1. The number for the initial virus data.
DOI: 10.6084/m9.figshare.16864897.v1
title: Additional file 1 of Prediction of pandemic risk for animal-origin coronavirus using a deep learning method

description: Additional file 1. The number for the initial virus data.
DOI: 10.6084/m9.figshare.16864900
title: Additional file 2 of Prediction of pandemic risk for animal-origin coronavirus using a deep learning method

description: Additional file 2. The dataset for six virus types.
DOI: 10.6084/m9.figshare.16864900.v1
title: Additional file 2 of Prediction of pandemic risk for animal-origin coronavirus using a deep learning method

description: Additional file 2. The dataset for six virus types.
DOI: 10.6084/m9.figshare.16864903
title: Additional file 3 of Prediction of pandemic risk for animal-origin coronavirus using a deep learning method

description: Additional file 3. The Entry ID for the selected negative virus to recombine initial positive virus.
DOI: 10.6084/m9.figshare.16864906
title: Additional file 4 of Prediction of pandemic risk for animal-origin coronavirus using a deep learning method

description: Additional file 4. The number of virus data with artificial negative data.
DOI: 10.6084/m9.figshare.16864906.v1
title: Additional file 4 of Prediction of pandemic risk for animal-origin coronavirus using a deep learning method

description: Additional file 4. The number of virus data with artificial negative data.
DOI: 10.6084/m9.figshare.16864903.v1
title: Additional file 3 of Prediction of pandemic risk for animal-origin coronavirus using a deep learning method

description: Additional file 3. The Entry ID for the selected negative virus to recombine initial positive virus.
DOI: 10.6084/m9.figshare.16864918
title: Additional file 1 of A machine learning classifier approach for identifying the determinants of under-five child undernutrition in Ethiopian administrative zones

description: Additional file 1: Implementation of different Supervised Machine Learning (SML) using R statistical software.
DOI: 10.6084/m9.figshare.16864918.v1
title: Additional file 1 of A machine learning classifier approach for identifying the determinants of under-five child undernutrition in Ethiopian administrative zones

description: Additional file 1: Implementation of different Supervised Machine Learning (SML) using R statistical software.
DOI: 10.6084/m9.figshare.16864981.v1
title: Additional file 1 of Population Structure of Nation-Wide Rice in Thailand

description: Additional file 1. The supplementary tables.
DOI: 10.6084/m9.figshare.16864981
title: Additional file 1 of Population Structure of Nation-Wide Rice in Thailand

description: Additional file 1. The supplementary tables.
DOI: 10.25442/hku.16864411
title: Digital dentistry manual.pdf

description: By the end of this digital dentistry course, students should be able to:<br>1. To understand the different file extensions and scanning equipment used in Digital Dentistry <br>2. To use the intraoral and extraoral scanners independently in their provision of treatments topatients<br><br>3. To discuss the advantages and disadvantages of digital impression in comparison with theanalogue<br><br>4. To understand the basic principles of designing RBB using Exocad 5. To be able to perform zirconia polishing inside and outside clinic
DOI: 10.5517/ccdc.csd.cc23txyt
title: CCDC 1961337: Experimental Crystal Structure Determination

description: Related Article: Bhriguram Das, Malay Dolai, Anamika Dhara, Subhabrata Mabhai, Atanu Jana, Satyajit Dey, Ajay Misra|2021|Anal. Sci. Adv.|2|447|doi:10.1002/ansa.202000165
DOI: 10.5517/ccdc.csd.cc282g72
title: CCDC 2087733: Experimental Crystal Structure Determination

description: Related Article: Chihiro Tsukano, Ryotaro Yagita, Takayoshi Heike, Tagwa A. Mohammed, Kazuya Nishibayashi, Kazuhiro Irie, Yoshiji Takemoto|2021|Angew.Chem.,Int.Ed.|60|23106|doi:10.1002/anie.202109786
DOI: 10.5517/ccdc.csd.cc282g83
title: CCDC 2087734: Experimental Crystal Structure Determination

description: Related Article: Chihiro Tsukano, Ryotaro Yagita, Takayoshi Heike, Tagwa A. Mohammed, Kazuya Nishibayashi, Kazuhiro Irie, Yoshiji Takemoto|2021|Angew.Chem.,Int.Ed.|60|23106|doi:10.1002/anie.202109786
DOI: 10.5517/ccdc.csd.cc285r18
title: CCDC 2090889: Experimental Crystal Structure Determination

description: Related Article: Rongran Liang, Jayanta Samanta, Baihao Shao, Mingshi Zhang, Richard Staples, Albert Chen, Miao Tang, Yuyang Wu, Ivan Aprahamian, Chenfeng Ke|2021|Angew.Chem.,Int.Ed.|60|23176|doi:10.1002/anie.202109987
DOI: 10.5517/ccdc.csd.cc285r29
title: CCDC 2090890: Experimental Crystal Structure Determination

description: Related Article: Rongran Liang, Jayanta Samanta, Baihao Shao, Mingshi Zhang, Richard Staples, Albert Chen, Miao Tang, Yuyang Wu, Ivan Aprahamian, Chenfeng Ke|2021|Angew.Chem.,Int.Ed.|60|23176|doi:10.1002/anie.202109987
DOI: 10.5517/ccdc.csd.cc285yq4
title: CCDC 2091096: Experimental Crystal Structure Determination

description: Related Article: Rongran Liang, Jayanta Samanta, Baihao Shao, Mingshi Zhang, Richard Staples, Albert Chen, Miao Tang, Yuyang Wu, Ivan Aprahamian, Chenfeng Ke|2021|Angew.Chem.,Int.Ed.|60|23176|doi:10.1002/anie.202109987
DOI: 10.5517/ccdc.csd.cc286h22
title: CCDC 2091603: Experimental Crystal Structure Determination

description: Related Article: Ryosuke Usui, Yusuke Sunada|2021|Inorg.Chem.|60|15101|doi:10.1021/acs.inorgchem.1c02043
DOI: 10.5517/ccdc.csd.cc28dngt
title: CCDC 2097536: Experimental Crystal Structure Determination

description: Related Article: Milan Pramanik, Ashis Mathuri, Sudip Sau, Monojit Das, Prasenjit Mal|2021|Org.Lett.|23|8088|doi:10.1021/acs.orglett.1c03100
DOI: 10.5517/ccdc.csd.cc28flbn
title: CCDC 2098431: Experimental Crystal Structure Determination

description: Related Article: Marco A. Henriquez, Sebastian Engl, Pablo Jaque, Ivan A. Gonzalez, Mirco Natali, Oliver Reiser, Alan R. Cabrera|2021|Eur.J.Inorg.Chem.|2021|4020|doi:10.1002/ejic.202100634
DOI: 10.5517/ccdc.csd.cc28flx7
title: CCDC 2098449: Experimental Crystal Structure Determination

description: Related Article: Marco A. Henriquez, Sebastian Engl, Pablo Jaque, Ivan A. Gonzalez, Mirco Natali, Oliver Reiser, Alan R. Cabrera|2021|Eur.J.Inorg.Chem.|2021|4020|doi:10.1002/ejic.202100634
DOI: 10.5517/ccdc.csd.cc28flz9
title: CCDC 2098451: Experimental Crystal Structure Determination

description: Related Article: Marco A. Henriquez, Sebastian Engl, Pablo Jaque, Ivan A. Gonzalez, Mirco Natali, Oliver Reiser, Alan R. Cabrera|2021|Eur.J.Inorg.Chem.|2021|4020|doi:10.1002/ejic.202100634
DOI: 10.5517/ccdc.csd.cc28fnbq
title: CCDC 2098493: Experimental Crystal Structure Determination

description: Related Article: Marco A. Henriquez, Sebastian Engl, Pablo Jaque, Ivan A. Gonzalez, Mirco Natali, Oliver Reiser, Alan R. Cabrera|2021|Eur.J.Inorg.Chem.|2021|4020|doi:10.1002/ejic.202100634
DOI: 10.5517/ccdc.csd.cc28n0kj
title: CCDC 2104607: Experimental Crystal Structure Determination

description: Related Article: Yong Yang, Shangxiong Huangfu, Sota Sato, Michal Juríček|2021|Org.Lett.|23|7943|doi:10.1021/acs.orglett.1c02950
DOI: 10.5517/ccdc.csd.cc28n0lk
title: CCDC 2104608: Experimental Crystal Structure Determination

description: Related Article: Yong Yang, Shangxiong Huangfu, Sota Sato, Michal Juríček|2021|Org.Lett.|23|7943|doi:10.1021/acs.orglett.1c02950
DOI: 10.5517/ccdc.csd.cc28n0ml
title: CCDC 2104609: Experimental Crystal Structure Determination

description: Related Article: Yong Yang, Shangxiong Huangfu, Sota Sato, Michal Juríček|2021|Org.Lett.|23|7943|doi:10.1021/acs.orglett.1c02950
DOI: 10.18112/openneuro.ds003855.v1.0.0
title: Capacity for movement is a major organisational principle in object representations: EEG data from Experiment 2
DOI: 10.34740/kaggle/dsv/2738433
title: Covid-19 in Singapore : Latest Detailed Data
DOI: 10.5281/zenodo.5595564
title: The intracranial tumor segmentation challenge: ICTS 2021-image labels

description: This dataset was retrieved from clinical work of radiosurgery. It contains brain tumor labels of 150 patients.
DOI: 10.5281/zenodo.5595563
title: The intracranial tumor segmentation challenge: ICTS 2021-image labels

description: This dataset was retrieved from clinical work of radiosurgery. It contains brain tumor labels of 150 patients.
DOI: 10.5281/zenodo.5595574
title: Dataset of first appearances of the scholarly bibliographic references on English Wikipedia articles as of 1 March 2017

description: <strong>Abstract</strong> We developed a methodology to detect the oldest scholarly reference added to Wikipedia articles by which a certain paper is uniquely identifiable as the "first appearance of the scholarly reference." We identified the first appearances of 923,894 scholarly references (611,119 unique DOIs) in180,795 unique pages on English Wikipedia as of March 1, 2017, and stored them in the dataset. Moreover, we assessed the precision of the dataset, which was and it was a high precision regardless of the research field. <strong>Data Records</strong> The data format of the dataset is JSON lines, where each line is a single record. In this dataset, we detected the first appearance of each scholarly reference added to Wikipedia articles. If there are multiple references corresponding to the same paper on the same page, only the oldest one is collected. Sample of the record is the following. doi -- DOI corresponding to the paper (String), e.g., "10.1006/anbe.1996.0497" paper_type -- Document type of the paper (String), e.g., "journal-article" paper_container_title -- Journal title, book title, or proceedings title (Array of String), e.g., ["Animal Behaviour"] paper_publisher -- Publisher name (String), e.g., "Elsevier BV" paper_title -- Paper title (Array of String), e.g., ["Push or pull: an experimental study on imitation in marmosets"] paper_published_year -- Published year (String), e.g., "1997" paper_issue -- Issue number (String), e.g., "4" paper_volume -- Volume number (String), e.g., "54" paper_page -- Page numbers (String), e.g., "817-831" paper_author -- Authors information consisted of given and family names, sequences (order in author names), and affiliations (Array of JSON), e.g., [{"given":"THOMAS", "family":"BUGNYAR", "sequence":"first", "affiliation":[]}, {"given":"LUDWIG", "family":"HUBER", "sequence":"additional", "affiliation":[]}] issn -- ISSN related to the paper (Array of String), e.g., ["0003-3472"] research_field -- Research fields from ESI categories (Array of String), e.g., ["PLANT & ANIMAL SCIENCE"] page_id -- Page id (String), e.g., "577858" page_title -- Page title (String), e.g., "Imitation" revision_id -- Revision id (String), e.g., "203309031" revision_timestamp -- Revision timestamp (String), e.g., "2008-04-04 15:54:09 UTC" revision_comment -- Revision comment (edit summary) (String), e.g., "/* Animal Behaviour */" editor_name -- Wikipedia editor's name (String), e.g., "Nicemr" editor_type -- Type of the editor (String), e.g., "User" <strong>References</strong> Kikkawa, J., Takaku, M. & Yoshikane, F. Dataset of first appearances of the scholarly bibliographic references on Wikipedia articles (submitted to <em>Scientific Data</em>). <strong>FUNDING</strong> JSPS KAKENHI Grant Number JP20K12543 JSPS KAKENHI Grant Number JP21K21303
DOI: 10.6084/m9.figshare.12769817
title: Dataset of first appearances of the scholarly bibliographic references on English Wikipedia articles as of 1 March 2017

description: This dataset has been moved to Zenodo (https://doi.org/10.5281/zenodo.5595573) due to the license issue.
DOI: 10.6084/m9.figshare.12769817.v2
title: Dataset of first appearances of the scholarly bibliographic references on English Wikipedia articles as of 1 March 2017

description: This dataset has been moved to Zenodo (https://doi.org/10.5281/zenodo.5595573) due to the license issue.