cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17755167
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model EC-EARTH3, scenario ssp126 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755166
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model EC-EARTH3, scenario ssp126 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755181
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model EC-EARTH3, scenario ssp245 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755182
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model EC-EARTH3, scenario ssp245 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755191
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model EC-EARTH3, scenario ssp370 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755190
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model EC-EARTH3, scenario ssp370 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755192
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model EC-EARTH3, scenario ssp585 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755193
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model EC-EARTH3, scenario ssp585 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17750471
title: Martian SLAMS database 2015-2019

description: This is a database of Short Large-Amplitude Magnetic Structures (SLAMS) identified at theMartian bow shock with MAVEN during the years 2015-2019

The SLAMS identification is done through an automated algorithm which uses the following criteria:-A magnetic amplitude that is twice the background magnetic field-An elliptical polarisation
DOI: 10.5281/zenodo.17750472
title: Martian SLAMS database 2015-2019

description: This is a database of Short Large-Amplitude Magnetic Structures (SLAMS) identified at theMartian bow shock with MAVEN during the years 2015-2019

The SLAMS identification is done through an automated algorithm which uses the following criteria:-A magnetic amplitude that is twice the background magnetic field-An elliptical polarisation
DOI: 10.6084/m9.figshare.30751190
title: Insomnia_ALPS

description: Raw data of insomnia and the ALPS index
DOI: 10.6084/m9.figshare.30751190.v1
title: Insomnia_ALPS

description: Raw data of insomnia and the ALPS index
DOI: 10.57745/b7xwm7
title: Barrage_Model_Rhone_OSR.var

description: :unav
DOI: 10.57745/fshehw
title: Model_Rhône_OSR.mge

description: :unav
DOI: 10.57745/ptwk5i
title: Notice_technique_Model_Rhône_OSR.pdf

description: :unav
DOI: 10.57745/uue7ro
title: pamhyr41.jar

description: :unav
DOI: 10.57745/ik4ohu
title: Notice_technique_Model_Rhone_OSR.pdf

description: :unav
DOI: 10.57745/2s7mer
title: Notice_technique_Model_Rhone_OSR.pdf

description: :unav
DOI: 10.5281/zenodo.17755202
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model MPI-ESM1-2-HR, scenario Historical -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755201
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model MPI-ESM1-2-HR, scenario Historical -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.34808/3fwx-qw91
title: OntoValidate: OntoNotes 5.0 NER validation dataset

description: OntoValidate dataset consists of 603 randomly chosen raw textsfrom the original OntoNote 5.0 dataset (3637 raw texts in total).
All raw texts are split into 13 subsets. Each subset was manuallyannotated with named entities by at least 10 people. Each annotator followed the official annotation guidelines (OntoNotes Named Entity Guidelines VERSION 14.0)that are distributed together with the OntoNotes 5.0 dataset. 
The OntoValidate dataset allows for a comparison of how different peopleunderstand the named entity recognition task. On the other hand, it also gave ussome insights about the precision of annotation guidelines itself.
Format
Each directory of the OntoValidate dataset represents a separate annotator.The first number in the directory name is the sequence number of the subset, the second isthe sequence number of the annotator. Each directory contains the JSON files that containthe annotations in spaCy JSON format. 
All annotations were created using the NER Text Annotator tool (https://tecoholic.github.io/ner-annotator/).
DOI: 10.5281/zenodo.17755213
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model MPI-ESM1-2-HR, scenario ssp126 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755212
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model MPI-ESM1-2-HR, scenario ssp126 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755222
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model MPI-ESM1-2-HR, scenario ssp245 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755221
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model MPI-ESM1-2-HR, scenario ssp245 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17776547
title: 宮崎県椎葉村尾前方言の自然談話「獣害の話」

description: 宮崎県椎葉村尾前方言の自然談話データです。

作成者は九州大学の廣澤尚之、録音日は2025年2月19日、尾前方言を母語とする80代女性O.Fさんの自然談話です。

研究・教育目的以外での利用はお控えください。
DOI: 10.5281/zenodo.17776546
title: 宮崎県椎葉村尾前方言の自然談話「獣害の話」

description: 宮崎県椎葉村尾前方言の自然談話データです。

作成者は九州大学の廣澤尚之、録音日は2025年2月19日、尾前方言を母語とする80代女性O.Fさんの自然談話です。

研究・教育目的以外での利用はお控えください。
DOI: 10.5281/zenodo.17755239
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model MPI-ESM1-2-HR, scenario ssp370 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755240
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model MPI-ESM1-2-HR, scenario ssp370 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755259
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model MPI-ESM1-2-HR, scenario ssp585 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755260
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model MPI-ESM1-2-HR, scenario ssp585 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755276
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level sfc, Global model CanESM5 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755277
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level sfc, Global model CanESM5 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755300
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level sfc, Global model EC-EARTH3 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755299
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level sfc, Global model EC-EARTH3 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.6084/m9.figshare.30751322
title: Supplementary material: Iron deficiency treatment pathway in Italy: patients’ perceptions of diagnosis and treatment

description: <b>These are peer-reviewed supplementary materials for the article</b><b> </b><b>'</b><b>Iron deficiency treatment pathway in Italy: patients’ perceptions of diagnosis and treatment</b><b>'</b><b> </b><b>published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><b>Survey questionnaire:</b>Screening questionsPatient's pathway<b>Aim:</b> This 2023 online survey assessed the management of patients with iron deficiency anemia/iron deficiency without anemia (IDA/IDWA) in Italy. <b>Materials & methods:</b> The study used the patient’s perspective to examine care pathways used to manage IDA/IDWA in Italy, to raise clinician awareness, improve patient care (earlier diagnosis, initiate appropriate treatment) and outcomes (reduce recurrence/progression). The survey questioned iron deficiency (ID) diagnoses of patients, their sources of information and influence, their knowledge of ID, perceptions and fears surrounding treatment, unmet needs and expectations, and underlying causes of treatment compliance and persistence. <b>Results:</b> Of the 404 respondents (102 males and 302 females) who completed the survey, all were aged between 18 and 80 years. Almost all respondents (97.0%) experienced ID symptoms, most frequently fatigue, weakness and tiredness (71.0% of the total cohort; 80.1% females vs 44.1% males); 76.8% of all respondents regarded symptoms as ‘bothersome’. Most respondents (70.5%) consulted a physician as the first action to treat ID (79.8% females vs 43.1% males); general practitioners were the main healthcare providers, consulted by 55.6% of all respondents. Most respondents (94.1%) were aware of potential ID recurrence, and 75.0% reported recurrent ID episodes since their diagnosis. Satisfaction with ID treatment was rated as average (7–7.7/10); 56.4% of all respondents stayed on ID treatment for as long as prescribed, and 41.1% did not fully comply with tablet intake, primarily because they ‘felt much better’ (64.8%).<b> Conclusion:</b> This survey identified high rates of self-reported ID symptoms and recurrent ID episodes among respondents. It highlights the importance of increasing awareness of ID and its consequences among healthcare practitioners and individuals in the general population, of shortening the time before diagnosis, and ensuring that patients continue treatment for the prescribed duration to resaturate serum iron levels.
DOI: 10.6084/m9.figshare.30751322.v1
title: Supplementary material: Iron deficiency treatment pathway in Italy: patients’ perceptions of diagnosis and treatment

description: <b>These are peer-reviewed supplementary materials for the article</b><b> </b><b>'</b><b>Iron deficiency treatment pathway in Italy: patients’ perceptions of diagnosis and treatment</b><b>'</b><b> </b><b>published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><b>Survey questionnaire:</b>Screening questionsPatient's pathway<b>Aim:</b> This 2023 online survey assessed the management of patients with iron deficiency anemia/iron deficiency without anemia (IDA/IDWA) in Italy. <b>Materials & methods:</b> The study used the patient’s perspective to examine care pathways used to manage IDA/IDWA in Italy, to raise clinician awareness, improve patient care (earlier diagnosis, initiate appropriate treatment) and outcomes (reduce recurrence/progression). The survey questioned iron deficiency (ID) diagnoses of patients, their sources of information and influence, their knowledge of ID, perceptions and fears surrounding treatment, unmet needs and expectations, and underlying causes of treatment compliance and persistence. <b>Results:</b> Of the 404 respondents (102 males and 302 females) who completed the survey, all were aged between 18 and 80 years. Almost all respondents (97.0%) experienced ID symptoms, most frequently fatigue, weakness and tiredness (71.0% of the total cohort; 80.1% females vs 44.1% males); 76.8% of all respondents regarded symptoms as ‘bothersome’. Most respondents (70.5%) consulted a physician as the first action to treat ID (79.8% females vs 43.1% males); general practitioners were the main healthcare providers, consulted by 55.6% of all respondents. Most respondents (94.1%) were aware of potential ID recurrence, and 75.0% reported recurrent ID episodes since their diagnosis. Satisfaction with ID treatment was rated as average (7–7.7/10); 56.4% of all respondents stayed on ID treatment for as long as prescribed, and 41.1% did not fully comply with tablet intake, primarily because they ‘felt much better’ (64.8%).<b> Conclusion:</b> This survey identified high rates of self-reported ID symptoms and recurrent ID episodes among respondents. It highlights the importance of increasing awareness of ID and its consequences among healthcare practitioners and individuals in the general population, of shortening the time before diagnosis, and ensuring that patients continue treatment for the prescribed duration to resaturate serum iron levels.
DOI: 10.5281/zenodo.17755341
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level sfc, Global model MPI-ESM1-2-HR -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755342
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level sfc, Global model MPI-ESM1-2-HR -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755366
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D3, Vertical level 10m, Global model CanESM5, scenario Historical -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.