Harnessing clinical annotations to improve deep learning performance in prostate segmentation is a dataset published in PLoS ONE (2021). On theSindex it has a DataRank of 0.539, placing it in the top 36.1% of the data-sharing corpus. It has been cited 10 times, with 8 citing works in its 1-hop citation network. Its calibrated FAIR score is 58/100.
Ranks in the top 36% for downstream scientific impact
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Full FAIR picture · advisory
The headline score is computed from the scored criteria — the fact-shaped checks (a repository, an accession, a licence) that two independent models agree on. The advisory criteria below are real FAIR guidance but rest on judgment calls that models read differently, so they inform without moving the number.
“10.5068/D1J09F”
The paper provides a DOI (10.5068/D1J09F) for the deposited summary statistics, which is a persistent identifier scheme.
RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit · RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier' · FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'
“Dryad repository”
The paper names the Dryad repository as the holder of the deposited data.
RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed ( · NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived · NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten
“The values behind the means, standard deviations and statistical tests reported are available on the Dryad repository with the DOI 10.5068/D1J09F”
The dataset identifier appears only in the body text of the data availability statement, not in the reference list. [majority verdict 'partial' (3/5 passes agreed)]
FORCE11 Joint Declaration of Data Citation Principles (2014) — data should be cited as a first- · RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes · FsF-F3-01M — F-UJI: 'Metadata includes the identifier of the data it describes'
Advisory · not in the published score
“The values behind the means, standard deviations and statistical tests reported are available on the Dryad repository with the DOI 10.5068/D1J09F”
The data availability statement points to a repository record (Dryad with DOI), which is a persistent repository link (Colavizza category 3). [majority verdict 'yes' (3/5 passes agreed)]
Colavizza, Hrynaszkiewicz, Staden, Whitaker & McGillivray (2020), 'The citation advantage of li · Springer Nature research data policy — Data Availability Statements: standard statement templat · RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes
“The values behind the means, standard deviations and statistical tests reported are available on the Dryad repository with the DOI 10.5068/D1J09F”
The dataset content is described in a single sentence rather than an itemised inventory, section, or table. [majority verdict 'partial' (3/5 passes agreed)]
RDA-F2-01M — 'Rich metadata is provided to allow discovery' (priority Essential) · FsF-F2-01M — F-UJI: 'Metadata includes descriptive core elements to support data findability' · FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'
“The values behind the means, standard deviations and statistical tests reported are available on the Dryad repository with the DOI 10.5068/D1J09F”
The Dryad repository is openly accessible without any stated precondition for the summary statistics deposited there. [majority verdict 'yes' (3/5 passes agreed)]
RDA-A1.1-01D — 'Data is accessible through a free access protocol' · FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data' · NSTC Desirable Characteristics of Data Repositories (2022) — 'Free and Easy Access'
Advisory · not in the published score
“The values behind the means, standard deviations and statistical tests reported are available on the Dryad repository with the DOI 10.5068/D1J09F”
The paper describes the action of accessing the data on Dryad but does not use an explicit access-level label such as 'open access' or 'publicly available'. [majority verdict 'partial' (3/5 passes agreed)]
FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data' · RDA-A1-01M — metadata contains information to enable the user to get access to the data · COAR Controlled Vocabularies — Access Rights v1.0 (open / embargoed / restricted / metadata-onl
The paper states that the clinical imaging data cannot be shared publicly due to privacy, but does not name any gatekeeper or access route for that data.
NIH Genomic Data Sharing Policy (NOT-OD-14-124) — controlled-access via a Data Access Committee · RDA-A1.2-01D — 'Data is accessible through an access protocol that supports authentication and · NIH DMS Policy Element 5 (NOT-OD-21-014) — Access, Distribution, or Reuse Considerations (conse
The paper does not mention any retention period, permanence, or timing of availability for the deposited data. [majority verdict 'no' (4/5 passes agreed)]
NIH DMS Plan Element 4 (NOT-OD-21-014) — Data Preservation, Access, and Associated Timelines · NSTC Desirable Characteristics (2022), Organizational Infrastructure: 'Retention Policy' · RDA-A2-01M — 'Metadata is guaranteed to remain available after data is no longer available'
The paper does not specify any file format for the deposited data.
FsF-R1.3-02D — F-UJI: 'Data is available in a file format recommended by the target research co · RDA-R1.3-02D — data is expressed in a machine-understandable community standard · RDA-I1-01D — data uses a knowledge representation expressed in a standardised format
Advisory · not in the published score
No data or metadata community standard (e.g., MIAME, BIDS, GO) is named in the paper.
RDA-R1.3-01M — 'Metadata complies with a community standard' (priority Essential) · RDA-R1.3-01D — 'Data complies with a community standard' · RDA-I2-01M — '(Meta)data use vocabularies that follow FAIR principles'
“The PROMISE12 grand challenge dataset is made available by its owners here: https://promise12.grand-challenge.org/”
The paper provides a repository URL for the PROMISE12 dataset, which is a qualified reference to an external resource. [majority verdict 'yes' (3/5 passes agreed)]
RDA-I3-01M — '(meta)data include references to other (meta)data' · RDA-I3-03M — 'metadata includes qualified references to other metadata' · FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'
No license is stated for the deposited data; the CC0 license applies to the article, not the data.
RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu · RDA-R1.1-02M — 'Metadata refers to a standard reuse licence' · RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'
No version token or date is provided for the deposited data snapshot.
DataCite Metadata Schema 4.6 — the 'Version' property · RDA-R1.2-01M — provenance information (which version was used is provenance) · NSTC Desirable Characteristics of Data Repositories (2022) — 'Provenance', 'Retention Policy'
The paper does not provide any locator for the study's own code; only third-party tools are named.
NIH DMS Policy Element 2 (NOT-OD-21-014) — 'Related Tools, Software and/or Code' · FAIR4RS Principles v1.0 (Chue Hong et al., 2022; RDA/FORCE11/ReSA) — FAIR Principles for Resear · FORCE11 Software Citation Principles (Smith, Katz & Niemeyer, 2016, PeerJ CS 2:e86)
“National Cancer Institute grant F30CA210329”
The paper lists specific grant numbers from named funders.
DataCite Metadata Schema 4.6 — 'FundingReference' property (funderName, funderIdentifier, award · Crossref Funder Registry — canonical funder identifiers for funding metadata · RDA-F2-01M — rich metadata provided to allow discovery (funding is part of the descriptive reco
Advisory · not in the published score
“3T magnet (Trio, Verio, or Skyra, Siemens Healthcare)”
The paper names specific instruments, platforms, and software used to generate the data.
RDA-R1.2-01M — 'Metadata includes provenance information according to community- specific standa · FsF-R1.2-01M — F-UJI: 'Metadata includes provenance information about data creation or generati · W3C PROV-O (W3C Recommendation, 2013) — the entity/activity/agent model of provenance
No README, data dictionary, or codebook is mentioned as accompanying the deposited data.
RDA-R1-01M — '(Meta)data are richly described with a plurality of accurate and relevant attribu · FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data' · NIH DMS Policy Element 3 (NOT-OD-21-014) — Standards (documentation and metadata to accompany t
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
Base Score Contribution
0.360
From this paper's citation signal
Citation Network Contribution
0.179
From 5 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 8 citers.
National Cancer Institute
Grant: F30CA210329
National Institute of General Medical Sciences
Grant: GM08042
National Cancer Institute
Grant: R21CA220352
National Cancer Institute
Grant: P50CA092131
National Cancer Institute
Grant: R01CA195505
National Cancer Institute
Grant: R01CA158627
National Cancer Institute
Grant: HHSN261200800001E
NIH
Grant: Intramural Research Program
NIGMS NIH HHS
Grant: T32 GM008042
CCR NIH HHS
Grant: HHSN261200800001C
NIBIB NIH HHS
Grant: T32 EB016640
NCI NIH HHS
Grant: P30 CA016042
National Institutes of Health
Grant: 5T32GM008042-27
Medical Scientist Training Program
National Institutes of Health
Grant: 5F30CA210329-03
Development of a Multimodal Deep Learning Model for the Generation of Cancer Probability Maps and Imaging Biomarkers for Prostate Cancer using Multiparametric MRI
National Institutes of Health
Grant: 5R21CA220352-02
Predicting the Presence of Clinically Significant Prostate Cancer using Multiparametric MRI and MR-US Fusion Biopsy
National Institutes of Health
Grant: 5P50CA092131-05
UCLA SPORE IN PROSTATE CANCER
National Institutes of Health
Grant: 5R01CA195505-02
Prospective Assessment of Image Registration for the Diagnosis of Prostate Cancer
National Institutes of Health
Grant: 1R01CA158627-01
Biopsy Tracking and MRI Fusion to Enhance Imaging of Cancer Within the Prostate
UCLA-Caltech Medical Scientist Training Program
FWCI
0.91
Citation Percentile
0.7%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Harnessing clinical annotations to improve deep learning performance in prostate segmentation
NCI-ISBI 2013 Challenge: Automated Segmentation of Prostate Structures (ISBI-MR-Prostate-2013)