cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7348263
title: ES-PT, Advanced driving, Complex manoeuvres: Automated Overtaking

description: Use Case Category: <strong>Advanced Driving</strong><br> User Story: <strong>Complex manoeuvres in cross-border settings</strong><br> Location: Spain-Portugal (ES-PT) cross-border corridor According to 3GPP TS 22.186 R16, Advanced Driving “enables semi-automated or fully-automated driving. Longer inter-vehicle distance is assumed. Each vehicle and/or Road Side Unit (RSU) shares data obtained from its local sensors with vehicles in proximity, thus allowing vehicles to coordinate their trajectories or manoeuvres. In addition, each vehicle shares its driving intention with vehicles in proximity. The benefits of this use case group are safer traveling, collision avoidance, and improved traffic efficiency”. Scenario 2: <strong>Automated Overtaking</strong>: When an automated vehicle needs to overtake a vehicle that precedes it, additional information provided by communication technologies will drastically improve and complement the information provided by its sensor constellation. There are many situations where the dimensions of other vehicles can cover the field of view of the autonomous vehicle sensors (for example, a truck can reduce the vision of a camera, a laser or a radar sensor). Moreover, according to the route followed by the vehicle, it can happen that a highway exit or a toll is near to the point where the overtaking takes place, and a queue of vehicles can complicate the scenario reducing free space and therefore producing a less appropriate manoeuvre. Other complex scenario can appear when there are vehicles behind the automated vehicles that occludes the vision of rear sensors. Considering that we are driving on a two-lane road with a right-hand traffic regulation, this occlusion can produce that the automated vehicle is not able to perceive a vehicle driving fast in the left lane. The purpose of this use case is to extend the 360º perception layer of the automated vehicle by integrating communication capabilities in the different vehicles of the scenario and additional road sensors (e.g. traffic radars) in the infrastructure. In this way, vehicles will be able to share their positions, speeds, sizes, etc., as well as the road-side infrastructure, helping automated vehicle to understand current situation and thus take the best decision of how to proceed with the automated overtaking.
DOI: 10.5281/zenodo.7348247
title: ES-PT, Advanced driving, Complex manoeuvres: lane merge

description: Use Case Category: <strong>Advanced Driving</strong><br> User Story: <strong>Complex manoeuvres in cross-border settings</strong><br> Location: Spain-Portugal (ES-PT) cross-border corridor According to 3GPP TS 22.186 R16, Advanced Driving “enables semi-automated or fully-automated driving. Longer inter-vehicle distance is assumed. Each vehicle and/or Road Side Unit (RSU) shares data obtained from its local sensors with vehicles in proximity, thus allowing vehicles to coordinate their trajectories or manoeuvres. In addition, each vehicle shares its driving intention with vehicles in proximity. The benefits of this use case group are safer traveling, collision avoidance, and improved traffic efficiency”. Scenario 1: <strong>Lane merge for automated vehicles</strong>: This scenario manages the situation where automated vehicles are in a lane merge scenario, analysing the traffic flow of the target lane. In this way, the system can detect existing vehicles including their lane position, acceleration, speed, size, etc. providing an extended perception layer, which is taken into account by the automated vehicle to determine the best merge manoeuvre according to the current situation. Vehicles in the lane to be merged are connected vehicles that share their vehicle data with the use of a Communication Unit with 5G capabilities and through a MEC Node. Road sensing technologies, such as traffic radars, are also used to detect the presence of vehicles in the target lane and to transmit their position and speed to the automated vehicle. Automated vehicle uses the Communication Unit as well in order to receive the information sent by surrounded vehicles and the road-side infrastructure, and therefore determine the status of the lane merge and the best way to operate to success in a safe and comfortable lane merge.
DOI: 10.5281/zenodo.7348248
title: ES-PT, Advanced driving, Complex manoeuvres: lane merge

description: Use Case Category: <strong>Advanced Driving</strong><br> User Story: <strong>Complex manoeuvres in cross-border settings</strong><br> Location: Spain-Portugal (ES-PT) cross-border corridor According to 3GPP TS 22.186 R16, Advanced Driving “enables semi-automated or fully-automated driving. Longer inter-vehicle distance is assumed. Each vehicle and/or Road Side Unit (RSU) shares data obtained from its local sensors with vehicles in proximity, thus allowing vehicles to coordinate their trajectories or manoeuvres. In addition, each vehicle shares its driving intention with vehicles in proximity. The benefits of this use case group are safer traveling, collision avoidance, and improved traffic efficiency”. Scenario 1: <strong>Lane merge for automated vehicles</strong>: This scenario manages the situation where automated vehicles are in a lane merge scenario, analysing the traffic flow of the target lane. In this way, the system can detect existing vehicles including their lane position, acceleration, speed, size, etc. providing an extended perception layer, which is taken into account by the automated vehicle to determine the best merge manoeuvre according to the current situation. Vehicles in the lane to be merged are connected vehicles that share their vehicle data with the use of a Communication Unit with 5G capabilities and through a MEC Node. Road sensing technologies, such as traffic radars, are also used to detect the presence of vehicles in the target lane and to transmit their position and speed to the automated vehicle. Automated vehicle uses the Communication Unit as well in order to receive the information sent by surrounded vehicles and the road-side infrastructure, and therefore determine the status of the lane merge and the best way to operate to success in a safe and comfortable lane merge.
DOI: 10.25318/36280001202201100002-eng
title: Youth life satisfaction during the COVID-19 pandemic in a cross-national comparison

description: Little is known about cross-national differences in the decline of youth life satisfaction during the COVID-19 pandemic. This study compares youth in Canada, Germany, Ireland, and the United Kingdom on life satisfaction before and during the pandemic.
DOI: 10.25318/36280001202201100001-fra
title: La syndicalisation au Canada, 1981 à 2022

description: L’économie canadienne a beaucoup évolué au cours des quatre dernières décennies. L’emploi s’est déplacé du secteur de la fabrication vers les secteurs de services. Les progrès technologiques ont permis au lieu de travail de tirer parti des technologies informatiques et depuis plus récemment, de la robotique et de l’intelligence artificielle. Les prix mondiaux du pétrole et des ressources naturelles ont fluctué de manière importante. Les conditions de travail ont considérablement changé depuis mars 2020 en raison des milliers d’employés qui ont commencé à travailler à domicile. Dans ce contexte changeant, comment les taux de syndicalisation ont-ils évolué au Canada au cours des quatre dernières décennies? Cet article s’appuie sur des données de l’Enquête sur l’activité en 1981 et de l’Enquête sur la population active pour répondre à cette question.
DOI: 10.25318/36280001202201100002-fra
title: La satisfaction des jeunes à l’égard de la vie durant la pandémie de COVID-19 selon une étude comparative transnationale

description: Nous en savons peu sur les différences transnationales associées à la baisse de satisfaction à l’égard de la vie chez les jeunes durant la pandémie de COVID-19. Cette étude compare le niveau de satisfaction à l’égard de la vie avant et durant la pandémie chez les jeunes du Canada, de l’Allemagne, de l’Irlande et du Royaume-Uni.
DOI: 10.25318/36280001202201100003-eng
title: Does taking short postsecondary programs or independent credits benefit recently displaced workers?

description: Workers who experience a permanent layoff (a job loss not followed by rejoining the same firm in the current or subsequent year) are often affected financially for several years. Based on the Longitudinal Worker File, the Postsecondary Student Information System, the 2006 Census of Population, and the T1 Family File the study examines the extent to which enrolling in or graduating from short, career-oriented programs or taking independent credits is associated with more favourable post-displacement earnings patterns compared to not enrolling at all.
DOI: 10.25381/cput.21608181.v1
title: Algorithm for voltage stability control in a power system with integrated microgrid

description: The Datasets are the configuration of the nine-bus system network in RSCAD, the design of different control logic and the simulation results of the integration of the photovoltaic system into the IEEE 9 bus system which was subject to a disturbance caused by an increase of 35% load increase. The results depict the effect of the load increase, the impact of the solar energy after adequate controller logic has been implemented to regulate the dispatch of the power from the photovoltaic into the electrical grid.
DOI: 10.25381/cput.21608181
title: Algorithm for voltage stability control in a power system with integrated microgrid

description: The Datasets are the configuration of the nine-bus system network in RSCAD, the design of different control logic and the simulation results of the integration of the photovoltaic system into the IEEE 9 bus system which was subject to a disturbance caused by an increase of 35% load increase. The results depict the effect of the load increase, the impact of the solar energy after adequate controller logic has been implemented to regulate the dispatch of the power from the photovoltaic into the electrical grid.
DOI: 10.5281/zenodo.7351492
title: Researcher survey data (European Research Data Landscape study)

description: Anonymised researcher survey data from the European Research Data Landscape study.
DOI: 10.25318/36280001202201100003-fra
title: Les programmes d’études postsecondaires courts ou les crédits hors programme sont-ils utiles pour les travailleurs qui ont récemment perdu leur emploi?

description: Une mise à pied permanente, c’est-à-dire une perte d’emploi non suivie d’une réembauche dans l’entreprise au cours de la même année ou de la suivante, affecte souvent les finances des travailleurs licenciés durant plusieurs années. S’appuyant sur des données du Fichier de données longitudinales sur la main-d’œuvre, du Système d’information sur les étudiants postsecondaires, du Recensement de la population de 2006 et du Fichier des familles T1, l’étude examine la mesure dans laquelle le fait de s’inscrire à des programmes courts axés sur la carrière ou à des programmes de formation autodidactique — ou d’obtenir un diplôme dans ces programmes — est associé à des tendances plus favorables en matière de perception de revenus après une perte d’emploi par rapport au fait de ne s’inscrire à aucun programme.
DOI: 10.57745/y5ufy1
title: Orthologous_collinear_regions_Lancer_ChineseSpring.bed
DOI: 10.57745/ltsh1t
title: Orthologous_collinear_regions_Zang1817_ChineseSpring.bed
DOI: 10.57745/9suzb9
title: Orthologous_collinear_regions_Aegilops_tauschii_ChineseSpring.bed
DOI: 10.57745/wiwmax
title: Orthologous_collinear_regions_ArinaLrFor_ChineseSpring.bed
DOI: 10.57745/w8fbmp
title: Orthologous_collinear_regions_Triticum_dicoccoides_ChineseSpring.bed
DOI: 10.57745/wh0kc2
title: Orthologous_collinear_regions_SY_Mattis_ChineseSpring.bed
DOI: 10.57745/3ijodj
title: Orthologous_collinear_regions_Spelt_ChineseSpring.bed
DOI: 10.57745/w60iqp
title: Orthologous_collinear_regions_Triticum_urartu_ChineseSpring.bed
DOI: 10.57745/69lndt
title: Orthologous_collinear_regions_Norin61_ChineseSpring.bed
DOI: 10.57745/l3748q
title: Orthologous_collinear_regions_Triticum_durum_ChineseSpring.bed
DOI: 10.57745/jb7u1a
title: Orthologous_collinear_regions_Julius_ChineseSpring.bed
DOI: 10.57745/mxqhvz
title: Orthologous_collinear_regions_Mace_ChineseSpring.bed
DOI: 10.57745/jxr8k1
title: Orthologous_collinear_regions_Jagger_ChineseSpring.bed
DOI: 10.57745/rex2uj
title: Orthologous_collinear_regions_Renan_ChineseSpring.bed
DOI: 10.57745/wamcgy
title: Orthologous_collinear_regions_Stanley_ChineseSpring.bed
DOI: 10.57745/hfbtbv
title: Orthologous_collinear_regions_Landmark_ChineseSpring.bed
DOI: 10.57745/km9zw1
title: Orthologous_genes_ChineseSpring_detected_inMace.bed
DOI: 10.57745/z6vfoq
title: Orthologous_genes_ChineseSpring_detected_inNorin61.bed
DOI: 10.57745/bpmg3y
title: Orthologous_genes_ChineseSpring_detected_inArinaLrFor.bed
DOI: 10.57745/muawgu
title: Orthologous_genes_ChineseSpring_detected_inRenan.bed
DOI: 10.57745/e5ixcn
title: Orthologous_genes_ChineseSpring_detected_inTriticum_urartu.bed
DOI: 10.57745/v6p3up
title: Orthologous_genes_ChineseSpring_detected_inSY_Mattis.bed
DOI: 10.57745/rxupmn
title: Orthologous_genes_ChineseSpring_detected_inLancer.bed
DOI: 10.57745/ajgy85
title: Orthologous_genes_ChineseSpring_detected_inZang1817.bed
DOI: 10.57745/ezxsbr
title: Orthologous_genes_ChineseSpring_detected_inStanley.bed
DOI: 10.57745/pxee7m
title: Orthologous_genes_ChineseSpring_detected_inTriticum_dicoccoides.bed
DOI: 10.57745/0fxjwi
title: Orthologous_genes_ChineseSpring_detected_inJagger.bed
DOI: 10.57745/otcqeb
title: Orthologous_genes_ChineseSpring_detected_inAegilops_tauschii.bed
DOI: 10.57745/udcft8
title: Orthologous_genes_ChineseSpring_detected_inSpelt.bed
DOI: 10.57745/2m4blq
title: Orthologous_genes_ChineseSpring_detected_inJulius.bed
DOI: 10.57745/m2aa0i
title: Orthologous_genes_ChineseSpring_detected_inLandmark.bed
DOI: 10.57745/z0ylxo
title: Orthologous_genes_ChineseSpring_detected_inTriticum_durum.bed
DOI: 10.57745/ec1ljt
title: Lancer_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/cmczfj
title: Landmark_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/x84igk
title: Stanley_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/zbu9f0
title: Renan_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/qdwawz
title: Aegilops_tauschii_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/8vtsex
title: Julius_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/yhwsmr
title: Triticum_urartu_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/5o1g8e
title: Jagger_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/jdvqeb
title: Mace_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/z4mx9s
title: ArinaLrFor_transposable_elements_annotation_ClariTE.gff3
DOI: 10.21227/1aqm-xr17
title: Reduced Corpus on Interactive Visualization on Large High-Resolution Displays

description: This data set is a selected list of publications on data visualization on large high-resolution display. We conducted a systematic search in six major scientific databases in computer science (Springer, Wiley Online Library, ScienceDirect, ACM digital library, IEEE Xplore, EBSCO host between November 23 and December 1, 2019) using 23 search queries capturing the different terms used to describe a wall-sized display (e.g. “visualization wall”, “tiled display”, etc.). While the original result set included 13613 records, this reduced 701-paper data set is the outcome of multiple rounds of data wrangling documented in details in the related survey paper.
DOI: 10.57745/wax5g5
title: Zhang1817_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/wsgu4w
title: SY_Mattis_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/uloidk
title: Norin61_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/1azkdc
title: Spelt_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/nhnjsr
title: Triticum_durum_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/i6d6fn
title: DVUploaderLog__1667810568005.log
DOI: 10.57745/yymwc3
title: Triticum_dicoccoides_transposable_elements_annotation_ClariTE.gff3
DOI: 10.57745/0llvy0
title: DVUploaderLog__1667810714460.log
DOI: 10.57745/9b1459
title: Recent_Insertions_TE_Zang1817.gff3
DOI: 10.57745/h6yzk7
title: Recent_Insertions_TE_Renan.gff3
DOI: 10.57745/rzepu4
title: Recent_Insertions_TE_Julius.gff3
DOI: 10.57745/ohjb1j
title: Recent_Insertions_TE_SY_Mattis.gff3
DOI: 10.57745/5h7o1n
title: Recent_Insertions_TE_Spelt.gff3
DOI: 10.57745/olrnfh
title: Recent_Insertions_TE_Landmark.gff3
DOI: 10.57745/xztu9n
title: Recent_Insertions_TE_Triticum_durum.gff3
DOI: 10.57745/h33zs4
title: Recent_Insertions_TE_Chinese_Spring.gff3
DOI: 10.57745/bykd4f
title: Recent_Insertions_TE_Mace.gff3
DOI: 10.57745/rrcsyn
title: Recent_Insertions_TE_Lancer.gff3
DOI: 10.57745/zhie5y
title: Recent_Insertions_TE_Stanley.gff3
DOI: 10.57745/6vrrpy
title: Recent_Insertions_TE_Triticum_dicoccoides.gff3
DOI: 10.57745/u0h93v
title: Recent_Insertions_TE_Norin61.gff3
DOI: 10.57745/fdcomg
title: Recent_Insertions_TE_Jagger.gff3
DOI: 10.57745/erfjmz
title: Recent_Insertions_TE_Aegilops_tauschii.gff3
DOI: 10.57745/rbgsua
title: Recent_Insertions_TE_Triticum_urartu.gff3
DOI: 10.57745/pedli5
title: Recent_Insertions_TE_ArinaLrFor.gff3
DOI: 10.57745/br18yr
title: Conserved_regions_Renan_ChineseSpring.bed
DOI: 10.57745/btayql
title: Conserved_regions_Stanley_ChineseSpring.bed
DOI: 10.57745/fedi3k
title: Conserved_regions_Triticum_durum_ChineseSpring.bed
DOI: 10.57745/yw6w0h
title: Conserved_regions_SY_Mattis_ChineseSpring.bed
DOI: 10.57745/pwjoff
title: Conserved_regions_Mace_ChineseSpring.bed
DOI: 10.57745/y0mnhw
title: Conserved_regions_Triticum_urartu_ChineseSpring.bed
DOI: 10.57745/cv8ftb
title: Conserved_regions_Landmark_ChineseSpring.bed
DOI: 10.57745/2kuwuz
title: Conserved_regions_Aegilops_tauschii_ChineseSpring.bed
DOI: 10.57745/4vfsya
title: Conserved_regions_Spelt_ChineseSpring.bed
DOI: 10.57745/kmedlm
title: Conserved_regions_Norin61_ChineseSpring.bed
DOI: 10.57745/xfa8ng
title: Conserved_regions_Triticum_dicoccoides_ChineseSpring.bed
DOI: 10.57745/qkwt1c
title: Conserved_regions_ArinaLrFor_ChineseSpring.bed
DOI: 10.57745/s3yepu
title: Conserved_regions_Jagger_ChineseSpring.bed
DOI: 10.57745/gnivof
title: Conserved_regions_Lancer_ChineseSpring.bed
DOI: 10.57745/nq1cyd
title: Conserved_regions_Julius_ChineseSpring.bed
DOI: 10.57745/d1ebvk
title: Conserved_regions_Zang1817_ChineseSpring.bed
DOI: 10.57745/p3yfc4
title: Specific_regions_ArinaLrFor.bed
DOI: 10.57745/o0zn1i
title: Specific_regions_ChineseSpring_Comparedto_Triticum_dicoccoides.bed
DOI: 10.57745/0su5bs
title: Specific_regions_ChineseSpring_Comparedto_Lancer.bed
DOI: 10.57745/qd58zz
title: Specific_regions_ChineseSpring_Comparedto_Zang1817.bed
DOI: 10.57745/vaxo8o
title: Specific_regions_ChineseSpring_Comparedto_Stanley.bed
DOI: 10.57745/rzhou2
title: Specific_regions_ChineseSpring_Comparedto_Triticum_urartu.bed
DOI: 10.57745/o1u0rh
title: Specific_regions_ChineseSpring_Comparedto_Renan.bed
DOI: 10.57745/5rn4tw
title: Specific_regions_ChineseSpring_Comparedto_Spelt.bed
DOI: 10.57745/3cftoq
title: Specific_regions_Triticum_durum.bed
DOI: 10.57745/9r50sz
title: Specific_regions_Spelt.bed
DOI: 10.57745/zmcfd9
title: Specific_regions_Julius.bed
DOI: 10.57745/pg2piz
title: Specific_regions_ChineseSpring_Comparedto_Norin61.bed
DOI: 10.57745/q6nmrd
title: Specific_regions_Triticum_urartu.bed
DOI: 10.57745/ygiseq
title: Specific_regions_ChineseSpring_Comparedto_Mace.bed
DOI: 10.34740/kaggle/dsv/4571366
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.57745/s7uzof
title: Specific_regions_ChineseSpring_Comparedto_SY_Mattis.bed
DOI: 10.57745/fl48df
title: Specific_regions_Aegilops_tauschii.bed
DOI: 10.57745/h2qbds
title: Specific_regions_Norin61.bed
DOI: 10.57745/5x09nz
title: Specific_regions_Stanley.bed
DOI: 10.57745/gujbjn
title: Specific_regions_ChineseSpring_Comparedto_Landmark.bed
DOI: 10.57745/9m4010
title: Specific_regions_Jagger.bed
DOI: 10.57745/ocdbm2
title: Specific_regions_SY_Mattis.bed
DOI: 10.57745/vfvtux
title: Specific_regions_Lancer.bed
DOI: 10.57745/piqmx7
title: Specific_regions_ChineseSpring_Comparedto_Julius.bed
DOI: 10.57745/glsxdc
title: Specific_regions_Triticum_dicoccoides.bed
DOI: 10.57745/ztba7s
title: Specific_regions_ChineseSpring_Comparedto_Jagger.bed
DOI: 10.57745/m2xoje
title: Specific_regions_ChineseSpring_Comparedto_Triticum_durum.bed
DOI: 10.57745/8x6nxq
title: Specific_regions_ChineseSpring_Comparedto_ArinaLrFor.bed
DOI: 10.57745/cdsxhp
title: Specific_regions_Renan.bed
DOI: 10.57745/btm9u9
title: Specific_regions_ChineseSpring_Comparedto_Aegilops_tauschii.bed
DOI: 10.57745/fkndxw
title: Specific_regions_Mace.bed
DOI: 10.57745/apuagj
title: Specific_regions_Landmark.bed
DOI: 10.57745/23xgh0
title: Specific_regions_Zang1817.bed
DOI: 10.23728/b2share.b36f78e35b4a42439f0e3730323cf8c3
title: GranParadiso - Snow Cover Duration - 2019/2020

description: Snow Cover Duration (SCD), First Snow Day (FSD), Last Snow Day (LSD) extracted from Sentinel-2 time series of years 2019 and 2020. The snow year is considered from the 1st September to 31st August of the following year. The snow season is considered continuous if at least 14 consecutive days of snow are detected. FSD: first day of a continuous snow season LSD: last day of a continuous snow season SCD: days between FSD and LSD of the same snow year (days)
description: Detection methodology used will be soon accessible
description: The final output consists of 20 m resolution raster layers in GeoTIFF format with the following values per pixel: FSD = first day of a continuous snow season, expressed as Day Of the Snow Year (DOYS) LSD = last day of a continuous snow season, expressed as Day Of the Snow Year (DOYS) SCD = number of days of continuous snow cover The SCD maps were validated against in situ data collected by weather stations equipped with snow gauges. The following metrics were computed: Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Bias Error (MBE). RMSE = 16.5 days MAE = 14 days MBE = 6.5 days
DOI: 10.6084/m9.figshare.21610437
title: Primary Dataset

description: This file contains full transcriptions to all research interviews as well as responses to research questionnaire.
DOI: 10.5281/zenodo.5734911
title: DeepLandforms: A Deep Learning Computer Vision toolset applied to a prime use case for mapping planetary skylights - ANc

description: Initial training dataset for <strong>DeepLandforms: A Deep Learning Computer Vision toolset applied to a prime use case for mapping planetary skylights</strong>
DOI: 10.5281/zenodo.5734912
title: DeepLandforms: A Deep Learning Computer Vision toolset applied to a prime use case for mapping planetary skylights - ANc

description: Initial training dataset for <strong>DeepLandforms: A Deep Learning Computer Vision toolset applied to a prime use case for mapping planetary skylights</strong>
DOI: 10.5281/zenodo.6818611
title: DeepLandforms: A Deep Learning Computer Vision toolset applied to a prime use case for mapping planetary skylights - ANc

description: Initial training dataset for <strong>DeepLandforms: A Deep Learning Computer Vision toolset applied to a prime use case for mapping planetary skylights</strong>
DOI: 10.25934/pr00001491.2
title: Available IPD datapackage for study 'A Phase 3, Randomized, Double-blind, Placebo-Controlled Study of Abiraterone Acetate (CB7630) Plus Prednisone in Asymptomatic or Mildly Symptomatic Patients With Metastatic Castration-Resistant Prostate Cancer'

description: This is a phase 3 study to compare the clinical benefit of abiraterone acetate plus prednisone with placebo plus prednisone in asymptomatic or mildly symptomatic patients with metastatic castration-resistant prostate cancer (CRPC).