{"doi":"10.3390/genes12111661","title":"Pairwise Correlation Analysis of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Dataset Reveals Significant Feature Correlation","abstract":"The Alzheimer’s Disease Neuroimaging Initiative (ADNI) contains extensive patient measurements (e.g., magnetic resonance imaging [MRI], biometrics, RNA expression, etc.) from Alzheimer’s disease (AD) cases and controls that have recently been used by machine learning algorithms to evaluate AD onset and progression. While using a variety of biomarkers is essential to AD research, highly correlated input features can significantly decrease machine learning model generalizability and performance. Additionally, redundant features unnecessarily increase computational time and resources necessary to train predictive models. Therefore, we used 49,288 biomarkers and 793,600 extracted MRI features to assess feature correlation within the ADNI dataset to determine the extent to which this issue might impact large scale analyses using these data. We found that 93.457% of biomarkers, 92.549% of the gene expression values, and 100% of MRI features were strongly correlated with at least one other feature in ADNI based on our Bonferroni corrected α (p-value ≤ 1.40754 × 10−13). We provide a comprehensive mapping of all ADNI biomarkers to highly correlated features within the dataset. Additionally, we show that significant correlation within the ADNI dataset should be resolved before performing bulk data analyses, and we provide recommendations to address these issues. We anticipate that these recommendations and resources will help guide researchers utilizing the ADNI dataset to increase model performance and reduce the cost and complexity of their analyses.","journal":"Genes","year":2021,"id":191415,"datarank":0.7512503417597537,"base_score":2.639057329615259,"endowment":2.639057329615259,"self_citation_contribution":0.3958585994422889,"citation_network_contribution":0.3553917423174648,"self_endowment_contribution":0.3958585994422889,"citer_contribution":0.3553917423174648,"corpus_percentile":73.18016554498337,"corpus_rank":3468,"citation_count":13,"citer_count":13,"citers_with_citation_signal":10,"citers_with_endowment":10,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8935,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":54.1667,"fair_percentile":68.66401712014674,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":621267,"name":"Matthew Hodgman","orcid":"0009-0005-3757-4141","position":1,"is_corresponding":false},{"id":757728,"name":"Brianna B. Greenwood","orcid":null,"position":2,"is_corresponding":false},{"id":757729,"name":"Devorah O. Stucki","orcid":null,"position":3,"is_corresponding":false},{"id":757730,"name":"Katrisa M. Ward","orcid":null,"position":4,"is_corresponding":false},{"id":694121,"name":"Mark Ebbert","orcid":"0000-0001-9158-4440","position":5,"is_corresponding":false},{"id":54266,"name":"John S. K. Kauwe","orcid":"0000-0001-8641-2468","position":6,"is_corresponding":false},{"id":265450,"name":"the Alzheimer’s Disease Neuroimaging Initiative","orcid":null,"position":7,"is_corresponding":false},{"id":415546,"name":"Justin Miller","orcid":"0000-0002-5309-1570","position":8,"is_corresponding":false},{"id":757011,"name":"Erik D. Huckvale","orcid":"0000-0002-6994-8831","position":0,"is_corresponding":true}],"reference_count":34,"raw_metadata":null,"created_at":"2026-07-18T23:49:35.285023Z","pmid":"34828267","pmcid":"PMC8619902","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":50.0,"fair_a":62.5,"fair_i":20.0,"fair_r":33.3333,"fair_zscore":0.7804,"fair_rationale":{"fair_score":54.17,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":50.0,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"The complete table (gene expression and MRI features included in addition to ADNIMERGE) for the Bonferroni corrected α is available online at: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv","grounded":true,"rationale":"The paper provides URLs for the data, not a persistent identifier from a recognised PID scheme. [majority verdict 'partial' (4/5 passes agreed)]","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":0.5,"verdict":"partial","evidence":"https://github.com/jmillerlab/ADNI_Correlation","grounded":true,"rationale":"The data are hosted on GitHub and Google Drive, which are code-repository and file-hosting services, not dedicated data repositories listed in re3data/FAIRsharing. [majority verdict 'partial' (4/5 passes agreed)]","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":"All custom scripts for processing and analyzing our data are available online at: https://github.com/jmillerlab/ADNI_Correlation . The tables containing the numbers of correlated features for each feature in our constructed data set are available online at: Bonferroni corrected α: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv . Maximally significant α: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/maximum-sig-freqs.csv . The pickle file containing the mapping of non-MRI features to the non-MRI features that they are correlated with is available online at: https://drive.google.com/file/d/1uRuT6rhDVDeeBuRYPif3Ate3u1UVs-hO/view?usp=sharing","grounded":true,"rationale":"The data availability statement points to URLs on GitHub and Google Drive, which are web addresses but not persistent identifiers or repository records with accessions, placing it in Colavizza category 3 but without a PID. [majority verdict 'partial' (4/5 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 complete table (gene expression and MRI features included in addition to ADNIMERGE) for the Bonferroni corrected α is available online at: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv","grounded":true,"rationale":"The dataset's content is described only in running prose, not in a structured itemised inventory such as a section or table listing files. [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":0.5,"verdict":"partial","evidence":"The complete table (gene expression and MRI features included in addition to ADNIMERGE) for the Bonferroni corrected α is available online at: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv","grounded":true,"rationale":"The dataset URL appears only in the body text (data availability statement), not as a reference-list entry. [majority verdict 'partial' (4/5 passes agreed)]","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":62.5,"criteria":[{"key":"a_data_openly_accessible","label":"Access route free of preconditions","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"The complete table (gene expression and MRI features included in addition to ADNIMERGE) for the Bonferroni corrected α is available online at: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv","grounded":true,"rationale":"The data are stated to be 'available online' at URLs with no precondition, embargo, or required application. [majority verdict 'yes' (4/5 passes agreed)]","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 complete table (gene expression and MRI features included in addition to ADNIMERGE) for the Bonferroni corrected α is available online at: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv","grounded":true,"rationale":"The text states the data are available online at URLs, implying an action to download, but uses no explicit access-level label such as 'open access' or 'publicly available'. [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":null,"grounded":false,"rationale":"The study's own data are aggregate correlation tables and derived files, not sensitive human-subject data; no gatekeeper is named.","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 states how long the data will remain available or makes any retention commitment. [majority verdict 'no' (4/5 passes agreed)]","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":null,"grounded":false,"rationale":"The paper names CSV as a format, which is an open, community-standard format. [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 community data or metadata standard (e.g., MIAME, BIDS) 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 (DOI, accession, RRID) is given for any external resource the study used; references to ADNI, ADNIMERGE, etc., are bare names or URLs. [majority verdict 'no' (4/5 passes agreed)]","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":33.33,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper only licenses the article (CC BY), not the data; no license is attached to the deposited data files.","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":0.5,"verdict":"partial","evidence":"We trained separate autoencoders for each of the 124 slice indices of the MRI sequences using the Adam optimizer for artificial neural networks","grounded":false,"rationale":"The text names specific software (PyTorch, Adam optimizer, etc.) and instruments used to produce the data. [downgraded to 'partial' — no verifiable quote from the paper]","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 README, data dictionary, or codebook is named as accompanying the data; variable definitions are only inside the article text. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","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 study's own data releases; the source data download date (15 November 2019) refers to ADNI, not the derived 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":1.0,"verdict":"yes","evidence":"All custom scripts for processing and analyzing our data are available online at: https://github.com/jmillerlab/ADNI_Correlation","grounded":true,"rationale":"The paper provides a GitHub repository URL for the study's own code, which is a machine-resolvable locator. [majority verdict 'yes' (4/5 passes agreed)]","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 work was supported by the BrightFocus Foundation [A2020118F to Miller] and the National Institutes of Health [1P30AG072946-01 to the University of Kentucky Alzheimer’s Disease Research Center].","grounded":true,"rationale":"The paper lists specific award numbers alongside funder names. [majority verdict 'yes' (4/5 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":"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":"The paper only licenses the article (CC BY), not the data; no license is attached to the deposited data files.","gain":16.67,"priority":"essential","scored":true},{"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 metabolomics data, deposit in MetaboLights (MTBLS accession) or Metabolomics Workbench.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The complete table (gene expression and MRI features included in addition to ADNIMERGE) for the Bonferroni corrected α is available online at: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv","why":"The paper provides URLs for the data, not a persistent identifier from a recognised PID scheme. [majority verdict 'partial' (4/5 passes agreed)]","gain":8.33,"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 metabolomics data, deposit in MetaboLights (MTBLS accession) or Metabolomics Workbench.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"https://github.com/jmillerlab/ADNI_Correlation","why":"The data are hosted on GitHub and Google Drive, which are code-repository and file-hosting services, not dedicated data repositories listed in re3data/FAIRsharing. [majority verdict 'partial' (4/5 passes agreed)]","gain":8.33,"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 metabolomics repository accession (e.g. from MetaboLights (MTBLS accession) or Metabolomics Workbench) in the reference list.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The complete table (gene expression and MRI features included in addition to ADNIMERGE) for the Bonferroni corrected α is available online at: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv","why":"The dataset URL appears only in the body text (data availability statement), not as a reference-list entry. [majority verdict 'partial' (4/5 passes agreed)]","gain":4.17,"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. 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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 study's own data releases; the source data download date (15 November 2019) refers to ADNI, not the derived 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":"All custom scripts for processing and analyzing our data are available online at: https://github.com/jmillerlab/ADNI_Correlation . The tables containing the numbers of correlated features for each feature in our constructed data set are available online at: Bonferroni corrected α: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv . Maximally significant α: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/maximum-sig-freqs.csv . The pickle file containing the mapping of non-MRI features to the non-MRI features that they are correlated with is available online at: https://drive.google.com/file/d/1uRuT6rhDVDeeBuRYPif3Ate3u1UVs-hO/view?usp=sharing","why":"The data availability statement points to URLs on GitHub and Google Drive, which are web addresses but not persistent identifiers or repository records with accessions, placing it in Colavizza category 3 but without a PID. [majority verdict 'partial' (4/5 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 complete table (gene expression and MRI features included in addition to ADNIMERGE) for the Bonferroni corrected α is available online at: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv","why":"The dataset's content is described only in running prose, not in a structured itemised inventory such as a section or table listing files. [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":"partial","current":0.5,"evidence":"The complete table (gene expression and MRI features included in addition to ADNIMERGE) for the Bonferroni corrected α is available online at: https://github.com/jmillerlab/ADNI_Correlation/blob/main/data/sig-freqs/bonferroni-sig-freqs.csv","why":"The text states the data are available online at URLs, implying an action to download, but uses no explicit access-level label such as 'open access' or 'publicly available'. [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 metabolomics, describe the data with ISA-Tab or Metabolomics Standards Initiative (MSI).","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No community data or metadata standard (e.g., MIAME, BIDS) 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":"partial","current":0.5,"evidence":"We trained separate autoencoders for each of the 124 slice indices of the MRI sequences using the Adam optimizer for artificial neural networks","why":"The text names specific software (PyTorch, Adam optimizer, etc.) and instruments used to produce the data. [downgraded to 'partial' — no verifiable quote from 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 README, data dictionary, or codebook is named as accompanying the data; variable definitions are only inside the article text. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","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":null,"why":"The study's own data are aggregate correlation tables and derived files, not sensitive human-subject data; no gatekeeper is named.","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 (DOI, accession, RRID) is given for any external resource the study used; references to ADNI, ADNIMERGE, etc., are bare names or URLs. [majority verdict 'no' (4/5 passes agreed)]","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 states how long the data will remain available or makes any retention commitment. [majority verdict 'no' (4/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["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.","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 metabolomics data, deposit in MetaboLights (MTBLS accession) or Metabolomics Workbench.","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 metabolomics data, deposit in MetaboLights (MTBLS accession) or Metabolomics Workbench.","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 metabolomics repository accession (e.g. from MetaboLights (MTBLS accession) or Metabolomics Workbench) in the reference list.","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 metabolomics formats such as mzML or nmrML."],"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":"2026-07-20T12:13:31.659371Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}