{"doi":"10.1002/ajpa.70066","title":"Technical Note: Using Machine Learning to Predict Locomotor Behavior in Great Apes and Humans From Femur Metaphyseal Shape","abstract":"OBJECTIVES: The morphology of the hominoid distal femoral metaphyseal surface has been demonstrated to reflect locomotor behavior throughout ontogeny. Here, we quantify metaphyseal surface morphology to evaluate its predictive relationship to locomotor behavioral modes in hominoids. MATERIALS AND METHODS: We collected three-dimensional (3D) surface laser scans of the femora of 177 human and great ape individuals representing all subadult stages of development. We used the landmark-free Global Point Signature (GPS) method to quantify the shape of the morphologically complex but amorphous metaphyseal surface. We then analyzed the GPS quantifications of shape using support vector machines (SVMs), a machine learning technique, to evaluate the predictive relationships between metaphyseal surface morphology and locomotor behavior in hominoids. RESULTS: We found that metaphyseal surface morphology is a strong predictor of locomotor behavior in hominoids. Our SVM, which relates nonambulation, bipedal walking, knuckle-walking, and climbing behavior with metaphyseal surface morphology, exhibits ~84% out-of-sample predictive accuracy. CONCLUSIONS: Our quantitative analyses confirm what has previously been qualitatively described-the metaphyseal surface of the distal femur is highly predictive of the locomotor behavior performed by hominoids during different stages of their lives. These results suggest that this region of the skeleton is suitable for reconstructing the locomotor behavior of extinct hominoid taxa.","journal":"American Journal of Biological Anthropology","year":2025,"id":544606,"datarank":0.11449306107463383,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.010520983990642026,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.010520983990642026,"corpus_percentile":28.158118666357236,"corpus_rank":9288,"citation_count":1,"citer_count":1,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.6673,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":12.5,"fair_percentile":28.767960868236013,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":477792,"name":"Abhijit J. Chaudhari","orcid":"0000-0002-4211-1900","position":1,"is_corresponding":false},{"id":774611,"name":"Mark N. Grote","orcid":"0000-0002-9031-8631","position":2,"is_corresponding":false},{"id":671289,"name":"Timothy D. Weaver","orcid":"0000-0003-0057-0663","position":3,"is_corresponding":false},{"id":1434728,"name":"Peter A. Stamos","orcid":"0000-0003-3487-1392","position":0,"is_corresponding":true}],"reference_count":41,"raw_metadata":null,"created_at":"2026-07-19T02:53:12.864581Z","pmid":"40462397","pmcid":"PMC12134525","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":0.0,"fair_a":25.0,"fair_i":0.0,"fair_r":25.0,"fair_zscore":-0.8688,"fair_rationale":{"fair_score":12.5,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":0.0,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No persistent identifier scheme is used for the dataset; the data are only in supplementary material.","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":null,"grounded":false,"rationale":"The data are held in the journal's supplementary material, not a dedicated repository. 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[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.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No persistent identifier scheme is used for the dataset; the data are only in supplementary material.","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.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The data are held in the journal's supplementary material, not a dedicated repository. 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[downgraded to 'no' — no verifiable quote from the paper]","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":"no","current":0.0,"evidence":null,"why":"The dataset is described in running prose rather than an itemised inventory. 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[downgraded to 'no' — no verifiable quote from the paper]","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.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No community data or metadata standard is named.","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. 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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 identifiers for external resources are provided, only grant numbers which are not data resources.","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 statement about the duration of data availability or retention commitment.","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.","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.","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.","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.","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."],"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":"2026-07-20T13:41:08.137040Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}