{"doi":"10.3390/tomography9020048","title":"Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning","abstract":"A murine model of myelofibrosis in tibia was used in a co-clinical trial to evaluate segmentation methods for application of image-based biomarkers to assess disease status. The dataset (32 mice with 157 3D MRI scans including 49 test-retest pairs scanned on consecutive days) was split into approximately 70% training, 10% validation, and 20% test subsets. Two expert annotators (EA1 and EA2) performed manual segmentations of the mouse tibia (EA1: all data; EA2: test and validation). Attention U-net (A-U-net) model performance was assessed for accuracy with respect to EA1 reference using the average Jaccard index (AJI), volume intersection ratio (AVI), volume error (AVE), and Hausdorff distance (AHD) for four training scenarios: full training, two half-splits, and a single-mouse subsets. The repeatability of computer versus expert segmentations for tibia volume of test-retest pairs was assessed by within-subject coefficient of variance (%wCV). A-U-net models trained on full and half-split training sets achieved similar average accuracy (with respect to EA1 annotations) for test set: AJI = 83-84%, AVI = 89-90%, AVE = 2-3%, and AHD = 0.5 mm-0.7 mm, exceeding EA2 accuracy: AJ = 81%, AVI = 83%, AVE = 14%, and AHD = 0.3 mm. The A-U-net model repeatability wCV [95% CI]: 3 [2, 5]% was notably better than that of expert annotators EA1: 5 [4, 9]% and EA2: 8 [6, 13]%. The developed deep learning model effectively automates murine bone marrow segmentation with accuracy comparable to human annotators and substantially improved repeatability.","journal":"Tomography","year":2023,"id":360319,"datarank":0.5572384591155644,"base_score":2.302585092994046,"endowment":2.302585092994046,"self_citation_contribution":0.3453877639491069,"citation_network_contribution":0.2118506951664574,"self_endowment_contribution":0.3453877639491069,"citer_contribution":0.2118506951664574,"corpus_percentile":64.92612361723525,"corpus_rank":4535,"citation_count":9,"citer_count":7,"citers_with_citation_signal":5,"citers_with_endowment":5,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.7046,"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":8.3333,"fair_percentile":26.47508407214919,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1112176,"name":"Rami F. Mourad","orcid":null,"position":1,"is_corresponding":false},{"id":337046,"name":"Kevin Heist","orcid":"0000-0001-5161-0608","position":2,"is_corresponding":false},{"id":1111756,"name":"Humera Tariq","orcid":"0000-0002-7684-9161","position":3,"is_corresponding":false},{"id":232085,"name":"Heang‐Ping Chan","orcid":"0000-0001-7777-9006","position":4,"is_corresponding":false},{"id":294968,"name":"Brian D. Ross","orcid":"0000-0003-2695-9140","position":5,"is_corresponding":false},{"id":246586,"name":"Thomas L. Chenevert","orcid":"0000-0003-1476-4274","position":6,"is_corresponding":false},{"id":336781,"name":"Dariya Malyarenko","orcid":"0000-0003-0403-1501","position":7,"is_corresponding":false},{"id":232086,"name":"Lubomir M. Hadjiiski","orcid":"0000-0003-2069-8066","position":8,"is_corresponding":false},{"id":1112175,"name":"Aman Kushwaha","orcid":null,"position":0,"is_corresponding":true}],"reference_count":36,"raw_metadata":null,"created_at":"2026-07-19T01:14:01.896928Z","pmid":"36961007","pmcid":"PMC10037585","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":12.5,"fair_i":20.0,"fair_r":25.0,"fair_zscore":-1.0337,"fair_rationale":{"fair_score":8.33,"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 mouse MHD image and annotation collection and tibia volume tables are available upon request.","grounded":true,"rationale":"No persistent identifier string is given for the dataset; the location is given in prose only.","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 mouse MHD image and annotation collection and tibia volume tables are available upon request.","grounded":true,"rationale":"No repository is named; the data are held by the authors and not deposited in a curated archive.","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 mouse MHD image and annotation collection and tibia volume tables are available upon request.","grounded":true,"rationale":"The DAS points to a person on request (Colavizza category 1), which is a partial artefact.","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 dataset (32 mice with 157 3D MRI scans including 49 test–retest pairs scanned on consecutive days) was split into approximately 70% training, 10% validation, and 20% test subsets.","grounded":true,"rationale":"The dataset content is described in running prose rather than an itemised inventory, making it a partial artefact.","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 for the dataset appears in the reference list or body text.","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":12.5,"criteria":[{"key":"a_data_openly_accessible","label":"Access route free of preconditions","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":"The mouse MHD image and annotation collection and tibia volume tables are available upon request.","grounded":true,"rationale":"The access route is a discretionary request to a person, which is not a followable route, so it is a no artefact.","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":0.5,"verdict":"partial","evidence":"The mouse MHD image and annotation collection and tibia volume tables are available upon request.","grounded":true,"rationale":"The DAS describes an action ('available upon request') without an explicit access-level label, so it is a partial artefact. [majority verdict 'partial' (4/5 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":0.0,"verdict":"no","evidence":"The mouse MHD image and annotation collection and tibia volume tables are available upon request.","grounded":true,"rationale":"The data are not identified as sensitive or human-subject, and no institutional gatekeeper is named; the only route is a personal request to the authors. [majority verdict 'no' (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 in the paper states 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":20.0,"criteria":[{"key":"i_open_nonproprietary_format","label":"Open file format","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"Conversion from the acquired scanner native 3D magnitude-valued 2dseq -image format to the meta-image header (MHD) ITK format was performed using custom routines in MATLAB.","grounded":false,"rationale":"The MHD format is an open, community-standard format, so it is a yes artefact. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","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 in the paper.","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 (e.g., another dataset, database, code) is given 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":25.0,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No license is named for the data; the article's CC BY license does not apply to 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":1.0,"verdict":"yes","evidence":"All mice were scanned using a fixed 3D FLASH coronal-plane imaging protocol on 7 T 30 cm bore Agilent system magnet with Small Receive CryoProbeTM4-Element Array RF Coil Kit, cryogenically cooled to 20–30 K.","grounded":true,"rationale":"The paper names the specific instrument and protocol used to produce the data, so it is a yes artefact.","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":"No documentation object (README, codebook, schema) is mentioned as accompanying the data.","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 is given for the dataset.","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":"The study's own code is not mentioned as available anywhere.","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":"This research was funded by National Institute of Health grant numbers R01CA238023, U24CA237683, R01CA190299, U01-CA232931, and R35CA197701.","grounded":true,"rationale":"Award numbers are given for the funding, so it is a yes artefact.","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 mouse MHD image and annotation collection and tibia volume tables are available upon request.","why":"No persistent identifier string is given for the dataset; the location is given in prose only.","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 mouse MHD image and annotation collection and tibia volume tables are available upon request.","why":"No repository is named; the data are held by the authors and not deposited in a curated archive.","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 mouse MHD image and annotation collection and tibia volume tables are available upon request.","why":"The access route is a discretionary request to a person, which is not a followable route, so it is a no artefact.","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 license is named for the data; the article's CC BY license does not apply to 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. 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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":"The study's own code is not mentioned as available anywhere.","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":"partial","current":0.5,"evidence":"Conversion from the acquired scanner native 3D magnitude-valued 2dseq -image format to the meta-image header (MHD) ITK format was performed using custom routines in MATLAB.","why":"The MHD format is an open, community-standard format, so it is a yes artefact. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","gain":4.17,"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 is given for the dataset.","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 mouse MHD image and annotation collection and tibia volume tables are available upon request.","why":"The DAS points to a person on request (Colavizza category 1), which is a partial artefact.","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 dataset (32 mice with 157 3D MRI scans including 49 test–retest pairs scanned on consecutive days) was split into approximately 70% training, 10% validation, and 20% test subsets.","why":"The dataset content is described in running prose rather than an itemised inventory, making it a partial artefact.","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":"partial","current":0.5,"evidence":"The mouse MHD image and annotation collection and tibia volume tables are available upon request.","why":"The DAS describes an action ('available upon request') without an explicit access-level label, so it is a partial artefact. [majority verdict 'partial' (4/5 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 in the paper.","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":"No documentation object (README, codebook, schema) is mentioned as accompanying the data.","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":"no","current":0.0,"evidence":"The mouse MHD image and annotation collection and tibia volume tables are available upon request.","why":"The data are not identified as sensitive or human-subject, and no institutional gatekeeper is named; the only route is a personal request to the authors. [majority verdict 'no' (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 (e.g., another dataset, database, code) is given 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 in the paper states 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":"2026-07-20T12:31:14.327377Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}