{"doi":"10.1097/ono.0000000000000028","title":"MRI Screening in Vestibular Schwannoma: A Deep Learning-based Analysis of Clinical and Audiometric Data","abstract":"Objective: To find a more objective method of assessing which patients should be screened for a vestibular schwannoma (VS) with magnetic resonance imaging (MRI) using a deep-learning algorithm to assess clinical and audiometric data. Materials and Methods: Clinical and audiometric data were collected for 592 patients who received an audiogram between January 2015 and 2020 at Duke University Health Center with and without VS confirmed by MRI. These data were analyzed using a deep learning-based analysis to determine if the need for MRI screening could be assessed more objectively with adequate sensitivity and specificity. Results: Patients with VS showed slightly elevated, but not statistically significant, mean thresholds compared to those without. Tinnitus, gradual hearing loss, and aural fullness were more common in patients with VS. Of these, only the presence of tinnitus was statistically significant. Several machine learning algorithms were used to incorporate and model the collected clinical and audiometric data, but none were able to distinguish ears with and without confirmed VS. When tumor size was taken into account the analysis was still unable to distinguish a difference. Conclusions: Using audiometric and clinical data, deep learning-based analyses failed to produce an adequately sensitive and specific model for the detection of patients with VS. This suggests that a specific pattern of audiometric asymmetry and clinical symptoms may not necessarily be predictive of the presence/absence of VS to a level that clinicians would be comfortable forgoing an MRI.","journal":"Otology & Neurotology Open","year":2023,"id":354713,"datarank":0.29188652235829704,"base_score":1.9459101490553132,"endowment":1.9459101490553132,"self_citation_contribution":0.29188652235829704,"citation_network_contribution":0.0,"self_endowment_contribution":0.29188652235829704,"citer_contribution":0.0,"corpus_percentile":43.93130656764911,"corpus_rank":7202,"citation_count":6,"citer_count":6,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8291,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":4.1667,"fair_percentile":4.891470498318557,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":328786,"name":"Shoujun Gu","orcid":"0000-0003-1041-3813","position":1,"is_corresponding":false},{"id":904040,"name":"Kathy Z. Dai","orcid":"0000-0002-3732-2092","position":2,"is_corresponding":false},{"id":1102737,"name":"Elizabeth Zhao","orcid":null,"position":3,"is_corresponding":false},{"id":1085773,"name":"Kristal M. Riska","orcid":"0000-0001-8159-1962","position":4,"is_corresponding":false},{"id":1091864,"name":"David M. Kaylie","orcid":null,"position":5,"is_corresponding":false},{"id":328789,"name":"Michael Hoa","orcid":"0000-0001-7469-2909","position":6,"is_corresponding":false},{"id":1102736,"name":"Sarah Kortebein","orcid":null,"position":0,"is_corresponding":true}],"reference_count":27,"raw_metadata":null,"created_at":"2026-07-19T01:13:11.976628Z","pmid":"38516318","pmcid":"PMC10950172","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":22.2222,"fair_a":6.25,"fair_i":0.0,"fair_r":8.3333,"fair_zscore":-1.1986,"fair_rationale":{"fair_score":4.17,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":22.22,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":"The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.","grounded":true,"rationale":"No persistent-identifier scheme string or URL is given for the data.","anchors":["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'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":"The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.","grounded":true,"rationale":"No repository is named; the data are held by the authors via the corresponding author.","anchors":["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"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.","grounded":true,"rationale":"The statement points to a person (Colavizza category 1), not a repository record, so partial. [majority verdict 'partial' (3/5 passes agreed)]","anchors":["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"],"scored":false,"signal":null},{"key":"f_discovery_metadata","label":"Description of the dataset as an object","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"The raw data set consisting of 1184 ears (592 patients) was then cleaned by filtering samples with error values.","grounded":true,"rationale":"The dataset's extent is described in running prose only, without an itemised inventory, so partial. [majority verdict 'partial' (3/5 passes agreed)]","anchors":["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'"],"scored":false,"signal":null},{"key":"f_dataset_cited","label":"Dataset formally cited","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No identifier or link for the dataset appears anywhere in the paper.","anchors":["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'"],"scored":true,"signal":null}]},"A":{"name":"Accessible","score":6.25,"criteria":[{"key":"a_data_openly_accessible","label":"Access route free of preconditions","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":"The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.","grounded":true,"rationale":"The only route offered is a discretionary request to a person, which is not a followable access route, so no.","anchors":["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'"],"scored":true,"signal":null},{"key":"a_access_conditions_stated","label":"Access level labelled","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":"answers","grounded":false,"rationale":"The paper states the data are not publicly available and describes an action (request to author) rather than using a standard access-rights label. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (2/5 passes agreed)]","anchors":["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"],"scored":false,"signal":null},{"key":"a_controlled_access_for_sensitive","label":"Gatekeeper for sensitive data","kind":"llm","weight":0.5,"fraction":0.5,"verdict":"partial","evidence":"The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.","grounded":true,"rationale":"The gatekeeper named is a natural person (the corresponding author), not an institutional body, so partial. [majority verdict 'partial' (3/5 passes agreed)]","anchors":["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"],"scored":false,"signal":null},{"key":"a_timeline_retention","label":"Availability timing & retention","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No sentence addresses when the data become available or how long they persist.","anchors":["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'"],"scored":false,"signal":null}]},"I":{"name":"Interoperable","score":0.0,"criteria":[{"key":"i_open_nonproprietary_format","label":"Open file format","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No file format is named for the released data.","anchors":["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"],"scored":true,"signal":null},{"key":"i_community_standard_vocabulary","label":"Community standard / vocabulary","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No data- or metadata-community standard is named for the study's own data.","anchors":["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'"],"scored":false,"signal":null},{"key":"i_qualified_references","label":"Identifiers for the resources the data depend on","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No identifier for any external resource (source dataset, reference database, etc.) appears in the text.","anchors":["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'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":8.33,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No licence or terms document is named for the data.","anchors":["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'"],"scored":true,"signal":null},{"key":"r_provenance_methods","label":"Provenance of the data","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No specific instrument, kit, or software used to produce the data is named; only analysis software is mentioned, which is not the production of the data. [majority verdict 'no' (2/5 passes agreed)]","anchors":["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"],"scored":false,"signal":null},{"key":"r_documentation_codebook","label":"Documentation / codebook","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"Neither a documentation object shipped with the data nor a variable-definition table inside the article exists.","anchors":["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"],"scored":false,"signal":null},{"key":"r_versioning","label":"Snapshot identified","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No version token or date pins a snapshot of the data.","anchors":["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'"],"scored":true,"signal":null},{"key":"x_code_availability","label":"Analysis code available","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"Neither a code repository URL, archive DOI, nor any other locator for the study's own code is provided.","anchors":["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)"],"scored":true,"signal":null},{"key":"x_funding_attribution","label":"Funder and award number","kind":"llm","weight":0.5,"fraction":1.0,"verdict":"yes","evidence":"ZIA DC000088","grounded":true,"rationale":"An award number (ZIA DC000088) is attached to the named funder (NIH/NIDCD), so yes. [majority verdict 'yes' (3/5 passes agreed)]","anchors":["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"],"scored":true,"signal":null}]}},"actions":[{"key":"f_dataset_pid","dimension":"F","label":"Persistent identifier for the data","action":"Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.","why":"No persistent-identifier scheme string or URL is given for the data.","gain":16.67,"priority":"essential","scored":true},{"key":"f_repository_named","dimension":"F","label":"Named repository","action":"Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.","why":"No repository is named; the data are held by the authors via the corresponding author.","gain":16.67,"priority":"essential","scored":true},{"key":"a_data_openly_accessible","dimension":"A","label":"Access route free of preconditions","action":"Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.","why":"The only route offered is a discretionary request to a person, which is not a followable access route, so no.","gain":16.67,"priority":"essential","scored":true},{"key":"r_reuse_license","dimension":"R","label":"Reuse licence","action":"Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No licence or terms document is named for the data.","gain":16.67,"priority":"essential","scored":true},{"key":"f_dataset_cited","dimension":"F","label":"Dataset formally cited","action":"Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the neuroimaging repository accession (e.g. from OpenNeuro or NeuroVault) in the reference list.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No identifier or link for the dataset appears anywhere in the paper.","gain":8.33,"priority":"important","scored":true},{"key":"i_open_nonproprietary_format","dimension":"I","label":"Open file format","action":"Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable. Prefer open neuroimaging formats such as NIfTI or BIDS.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No file format is named for the released data.","gain":8.33,"priority":"important","scored":true},{"key":"x_code_availability","dimension":"R","label":"Analysis code available","action":"Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI).","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"Neither a code repository URL, archive DOI, nor any other locator for the study's own code is provided.","gain":8.33,"priority":"important","scored":true},{"key":"r_versioning","dimension":"R","label":"Snapshot identified","action":"Version the deposit and cite the exact version analysed (a version-specific DOI, or an accession with its version suffix). A reader reproducing your work against 'the current release' is reproducing it against a different dataset.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No version token or date pins a snapshot of the data.","gain":4.17,"priority":"useful","scored":true},{"key":"f_data_availability_statement","dimension":"F","label":"Data-availability statement","action":"Replace the statement with the repository template: name the repository and give the accession or DOI (Colavizza category 3). This is the only DAS class associated with a measured citation advantage; 'available on reasonable request' and 'within the article' are not.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.","why":"The statement points to a person (Colavizza category 1), not a repository record, so partial. [majority verdict 'partial' (3/5 passes agreed)]","gain":0.0,"priority":"essential","scored":false},{"key":"f_discovery_metadata","dimension":"F","label":"Description of the dataset as an object","action":"Add a 'Data Records' section: itemise every file in the deposit and every variable or sample it holds, with counts and units. Describe the dataset as an object in its own right, not as a by-product of the findings — this is what makes it discoverable to someone who is not looking for your paper.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The raw data set consisting of 1184 ears (592 patients) was then cleaned by filtering samples with error values.","why":"The dataset's extent is described in running prose only, without an itemised inventory, so partial. [majority verdict 'partial' (3/5 passes agreed)]","gain":0.0,"priority":"essential","scored":false},{"key":"a_access_conditions_stated","dimension":"A","label":"Access level labelled","action":"State the access level in words, using the standard vocabulary: 'These data are open access' / 'These data are controlled access'. A reader — and a harvester — should not have to infer the access level from the presence of a download link.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"answers","why":"The paper states the data are not publicly available and describes an action (request to author) rather than using a standard access-rights label. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (2/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"i_community_standard_vocabulary","dimension":"I","label":"Community standard / vocabulary","action":"Adopt and NAME your domain's data standard — the minimum-information checklist, metadata schema, or ontology your community uses (MIAME/MINSEQE, ISA-Tab, BIDS, an OBO ontology, HL7 FHIR/OMOP) — and say which one you followed. A reporting checklist standardises your paper; it does nothing for your data. In neuroimaging, describe the data with BIDS, NIfTI or DICOM.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No data- or metadata-community standard is named for the study's own data.","gain":0.0,"priority":"important","scored":false},{"key":"r_provenance_methods","dimension":"R","label":"Provenance of the data","action":"Name the instruments, kits, and software — with versions — that produced the data, not just the verbs. 'Reads were aligned' is not provenance; 'aligned with STAR v2.7.9a to GRCh38' is, because someone else can rerun it.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No specific instrument, kit, or software used to produce the data is named; only analysis software is mentioned, which is not the production of the data. [majority verdict 'no' (2/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"r_documentation_codebook","dimension":"R","label":"Documentation / codebook","action":"Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. It is the cheapest single thing that makes a dataset usable by someone who was not in the lab, and a table buried in the article does not travel with the data.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"Neither a documentation object shipped with the data nor a variable-definition table inside the article exists.","gain":0.0,"priority":"important","scored":false},{"key":"a_controlled_access_for_sensitive","dimension":"A","label":"Gatekeeper for sensitive data","action":"Route sensitive data through an institutional gatekeeper — deposit in a controlled- access repository (dbGaP, EGA) with a Data Access Committee and a published DUA — rather than through the corresponding author's inbox. An author-gated dataset dies with the author's email address, and 'on reasonable request' has been shown repeatedly not to yield data.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.","why":"The gatekeeper named is a natural person (the corresponding author), not an institutional body, so partial. [majority verdict 'partial' (3/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false},{"key":"i_qualified_references","dimension":"I","label":"Identifiers for the resources the data depend on","action":"Cite by identifier every resource the data depend on — the source datasets' accessions, the reference build (GRCh38 / GCA_000001405.28), the cohort application number, the code DOI — and register those relations on the dataset record (IsDerivedFrom, IsSupplementTo). A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No identifier for any external resource (source dataset, reference database, etc.) appears in the text.","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No sentence addresses when the data become available or how long they persist.","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the neuroimaging repository accession (e.g. from OpenNeuro or NeuroVault) in the reference list."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-07-20T12:51:42.252235Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}