cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1438536.08fu
title: SH1438536.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1438537.08fu
title: SH1438537.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1438538.08fu
title: SH1438538.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1438539.08fu
title: SH1438539.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1438540.08fu
title: SH1438540.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1438541.08fu
title: SH1438541.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.25549/one-c4-27053
title: ONE, Inc. meeting minutes (1981)

description: ONE, Inc. minutes for the academic council meetings (1981)
DOI: 10.15156/bio/sh1438542.08fu
title: SH1438542.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1438543.08fu
title: SH1438543.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1438544.08fu
title: SH1438544.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1438545.08fu
title: SH1438545.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.7559183
title: chrysichthys_thysi_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7559182
title: chrysichthys_thysi_zanfona_1.fasta.gz

description: .
DOI: 10.6084/m9.figshare.21938234.v1
title: Do altmetric scores reflect article quality? Evidence from the UK Research Excellence Framework 2021: supplementary materials

description: Supplementary materials from the paper, "Do altmetric scores reflect article quality? Evidence from the UK Research Excellence Framework 2021" This consists of the raw data underlying the graphs in the paper and correlations and sample sizes for individual years and year ranges not presented in the paper. <br>
DOI: 10.6084/m9.figshare.21938234
title: Do altmetric scores reflect article quality? Evidence from the UK Research Excellence Framework 2021: supplementary materials

description: Supplementary materials from the paper, "Do altmetric scores reflect article quality? Evidence from the UK Research Excellence Framework 2021" This consists of the raw data underlying the graphs in the paper and correlations and sample sizes for individual years and year ranges not presented in the paper. <br>
DOI: 10.5281/zenodo.7559191
title: Dataset pertaining to the article "Serum levels of glial fibrillary acidic protein in patients with amyotrophic lateral sclerosis"

description: This is the dataset pertaining to the article "Serum levels of glial fibrillary acidic protein in patients with amyotrophic lateral sclerosis".
DOI: 10.5281/zenodo.7559190
title: Dataset pertaining to the article "Serum levels of glial fibrillary acidic protein in patients with amyotrophic lateral sclerosis"

description: This is the dataset pertaining to the article "Serum levels of glial fibrillary acidic protein in patients with amyotrophic lateral sclerosis".
DOI: 10.21227/d3de-q228
title: sss

description: ssss
DOI: 10.5281/zenodo.7559208
title: Impact of Code Language Models on Automated Program Repair (Dataset)

description: This is the fine-tuning dataset used in the paper Impact of Code Language Models on Automated Program Repair
DOI: 10.5281/zenodo.7559207
title: Impact of Code Language Models on Automated Program Repair (Dataset)

description: This is the fine-tuning dataset used in the paper Impact of Code Language Models on Automated Program Repair
DOI: 10.5281/zenodo.7559218
title: Chronic DBS of the NAcc region disrupts the stability of intertemporal preferences

description: Dataset for "Chronic DBS of the NAcc region disrupts the stability of intertemporal preferences". Shortterm intertemporal choice data corresponds to T2.1 vs T2.2 sessions in controls and DBS on vs. DBS off sessions in patients. Longterm intertemporal choice data corresponds to T1 vs pooled T2 sessions in controls and pre DBS vs. post DBS sessions in patients. For additional information please find the model code and readme file in the OSF repository (https://osf.io/53mkd/).
DOI: 10.5281/zenodo.7559217
title: Chronic DBS of the NAcc region disrupts the stability of intertemporal preferences

description: Dataset for "Chronic DBS of the NAcc region disrupts the stability of intertemporal preferences". Shortterm intertemporal choice data corresponds to T2.1 vs T2.2 sessions in controls and DBS on vs. DBS off sessions in patients. Longterm intertemporal choice data corresponds to T1 vs pooled T2 sessions in controls and pre DBS vs. post DBS sessions in patients. For additional information please find the model code and readme file in the OSF repository (https://osf.io/53mkd/).
DOI: 10.5281/zenodo.7559232
title: Argument-seeking conversations in german

description: This data set consists of ten conversations. The text files are the unedited transcripts of the conversations. The pdf files contain the conversations divided into their respective subtopics.
DOI: 10.5281/zenodo.7559231
title: Argument-seeking conversations in german

description: This data set consists of ten conversations. The text files are the unedited transcripts of the conversations. The pdf files contain the conversations divided into their respective subtopics.
DOI: 10.6084/m9.figshare.21914964
title: database.xlsx

description: this dataset was use for the paper titled "Response of nitrate leaching to no-tillage is dependent on soil, climate and management factors: a global meta-analysis".
DOI: 10.6084/m9.figshare.21914964.v1
title: database.xlsx

description: this dataset was use for the paper titled "Response of nitrate leaching to no-tillage is dependent on soil, climate and management factors: a global meta-analysis".
DOI: 10.5281/zenodo.7003924
title: SimuShips - A High Resolution Simulation Dataset for Ship Detection with Precise Annotations

description: <strong>SimuShips - A High Resolution Simulation Dataset for Ship Detection with Precise Annotations</strong> Availability of domain-specific datasets is a challenge for object detection. In particular, conducting onsite experiments is risky and time-consuming for the maritime domain. It is not always possible to capture challenging situations and incorporate variations in the environment. Therefore, we present a simulation-based dataset for maritime environments consisting of 9471 high-resolution (1920x1080) images resembling the real world with precise annotations. The dataset was acquired using a simulation tool, AILiveSim [17]. AILiveSim is a 3D simulation platform for targeted scalable development and integration of autonomous systems through digital twins. The tool provides a realistic 3D model of the route of the watercraft extended from the city of Turku to Ruisalo in South-West Finland. Our dataset incorporates diversity of objects, weather, illumination, visible proportion and scale in images that resemble the real world. Please cite the following publication when using the dataset: M. Raza, H. Prokopova, S. Huseynzade, S. Azimi and S. Lafond, "SimuShips - A High Resolution Simulation Dataset for Ship Detection with Precise Annotations," <em>OCEANS 2022, Hampton Roads</em>, Hampton Roads, VA, USA, 2022, pp. 1-5, doi: 10.1109/OCEANS47191.2022.9977182. The publication is available at: https://doi.org/10.1109/OCEANS47191.2022.9977182 A preprint version of the publication is available at https://arxiv.org/abs/2211.05237
DOI: 10.5281/zenodo.7003923
title: SimuShips - A High Resolution Simulation Dataset for Ship Detection with Precise Annotations

description: <strong>SimuShips - A High Resolution Simulation Dataset for Ship Detection with Precise Annotations</strong> Availability of domain-specific datasets is a challenge for object detection. In particular, conducting onsite experiments is risky and time-consuming for the maritime domain. It is not always possible to capture challenging situations and incorporate variations in the environment. Therefore, we present a simulation-based dataset for maritime environments consisting of 9471 high-resolution (1920x1080) images resembling the real world with precise annotations. The dataset was acquired using a simulation tool, AILiveSim [17]. AILiveSim is a 3D simulation platform for targeted scalable development and integration of autonomous systems through digital twins. The tool provides a realistic 3D model of the route of the watercraft extended from the city of Turku to Ruisalo in South-West Finland. Our dataset incorporates diversity of objects, weather, illumination, visible proportion and scale in images that resemble the real world. Please cite the following publication when using the dataset: M. Raza, H. Prokopova, S. Huseynzade, S. Azimi and S. Lafond, "SimuShips - A High Resolution Simulation Dataset for Ship Detection with Precise Annotations," <em>OCEANS 2022, Hampton Roads</em>, Hampton Roads, VA, USA, 2022, pp. 1-5, doi: 10.1109/OCEANS47191.2022.9977182. The publication is available at: https://doi.org/10.1109/OCEANS47191.2022.9977182 A preprint version of the publication is available at https://arxiv.org/abs/2211.05237
DOI: 10.6084/m9.figshare.3761562.v2466
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.5281/zenodo.7542519
title: Renta media por persona y nivel de formación en los 21 distritos del Ayuntamiento de Madrid (2016-2019)

description: El conjunto de datos "refomad-data.xlsx" ha sido utilizado en el proyecto REFOMAD. Incluye información sobre la renta media por persona, el nivel de formación educativa de los residentes mayores de 25 años y el número de centros educativos en cada uno de los 21 distritos del Ayuntamiento de Madrid durante los años 2016-2019. El nivel de formación tiene 6 niveles: no sabe leer ni escribir, bachiller elemental, formación profesional, titulados medios, estudios universitarios y nivel de estudios no consta. Los centros educativos se clasifican también en 6 niveles: escuelas infantiles municipales, escuelas infantiles públicas de la Comunidad Autónoma de Madrid, escuelas infantiles privadas, colegios públicos infantil/primaria, institutos públicos de educación secundaria y colegios privados infantil/primaria. Los datos de renta fueron proporcionados por el INE, los datos sobre la formación fueron obtenidos mediante encuestas propias realizadas por el equipo REFOMAD y los datos de los centros educativos fueron solicitados al portal de datos abiertos del Ayuntamiento de Madrid. Los datos están en formato XLSX y tienen un tamaño de 17 kB. Los datos fueron preprocesados y curados utilizando herramientas de software libre como NumPy y pandas en Python versión 3.10.6. Se incluyen adicionalmente los datos originales ("DATOS ORIGINALES.zip") y el script de Python empleado para la lectura, preprocesado, curación y análisis de los datos ("REFOMAD-ETL-CURATION.ipynb").
DOI: 10.5281/zenodo.7542518
title: Renta media por persona y nivel de formación en los 21 distritos del Ayuntamiento de Madrid (2016-2019)

description: El conjunto de datos "refomad-data.xlsx" ha sido utilizado en el proyecto REFOMAD. Incluye información sobre la renta media por persona, el nivel de formación educativa de los residentes mayores de 25 años y el número de centros educativos en cada uno de los 21 distritos del Ayuntamiento de Madrid durante los años 2016-2019. El nivel de formación tiene 6 niveles: no sabe leer ni escribir, bachiller elemental, formación profesional, titulados medios, estudios universitarios y nivel de estudios no consta. Los centros educativos se clasifican también en 6 niveles: escuelas infantiles municipales, escuelas infantiles públicas de la Comunidad Autónoma de Madrid, escuelas infantiles privadas, colegios públicos infantil/primaria, institutos públicos de educación secundaria y colegios privados infantil/primaria. Los datos de renta fueron proporcionados por el INE, los datos sobre la formación fueron obtenidos mediante encuestas propias realizadas por el equipo REFOMAD y los datos de los centros educativos fueron solicitados al portal de datos abiertos del Ayuntamiento de Madrid. Los datos están en formato XLSX y tienen un tamaño de 17 kB. Los datos fueron preprocesados y curados utilizando herramientas de software libre como NumPy y pandas en Python versión 3.10.6. Se incluyen adicionalmente los datos originales ("DATOS ORIGINALES.zip") y el script de Python empleado para la lectura, preprocesado, curación y análisis de los datos ("REFOMAD-ETL-CURATION.ipynb").
DOI: 10.25919/g3c4-7r75
title: Parkes observations for project P1165 semester 2022OCTS_04

description: We propose to confirm and time five pulsar candidates recently discovered by the Five-hundred-meter Aperture Spherical Telescope (FAST). These candidates were discovered during a pilot survey of an intermediate Galactic latitude region with six-minute pointings. One candidate, J1826-0049, has already been confirmed to be a 4.59 ms pulsar in a binary system with an orbital period of ~6.3 hr. The superior sensitivity of FAST has the potential to discover pulsars in compact binary systems and we propose to use Parkes to confirm the nature of these candidates. We also propose to time two of the brightest candidates with Parkes and measure their spin and orbital parameters. These observations have the potential to open new opportunities to probe exciting physics with these newly discovered pulsars.
DOI: 10.25919/wrcx-ne31
title: Parkes observations for project P737 semester 2022OCTS_05

description: The aim of this proposal is to carry out tests of the new backend instruments which cannot be carried out during standard maintenance periods. The scheduled time is used to measure beam shapes, determine polarisation calibration solutions and commission the National Facility observing modes for the new wide-band receiver.