{"id":"W2002120939","doi":"10.1249/mss.0000000000000588","title":"Enhancing a Somatic Maturity Prediction Model","year":2014,"lang":"en","type":"article","venue":"Medicine & Science in Sports & Exercise","topic":"Forensic Anthropology and Bioarchaeology Studies","field":"Arts and Humanities","cited_by":713,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; Vancouver Coastal Health; Vancouver Coastal Health Research Institute; University of British Columbia; University of Saskatchewan; Child and Family Research Institute","funders":"Canadian Institutes of Health Research","keywords":"Overfitting; Anthropometry; Statistics; Linear regression; Mathematics; Regression analysis; Mean squared error; Maturity (psychological); Medicine; Demography; Psychology; Developmental psychology; Internal medicine; Machine learning; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005940368,0.001027919,0.0008274052,0.0009224469,0.0005227789,0.001328595,0.001314922,0.0007503662,0.00217005],"category_scores_gemma":[0.01101092,0.0004439426,0.0009997302,0.0006970745,0.0004187474,0.0009306849,0.001474493,0.001796825,0.0007011868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008206806,"about_ca_system_score_gemma":0.001650359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01005649,"about_ca_topic_score_gemma":0.006243599,"domain_scores_codex":[0.9986565,0.0006416657,0.00005838904,0.0003832597,0.0001543278,0.0001059572],"domain_scores_gemma":[0.9958716,0.002833733,0.000279209,0.0002082339,0.0006646615,0.0001425465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003505939,0.0003604063,0.106239,0.0001478717,0.0004997263,0.0002731191,0.0003064215,0.7016789,0.001734132,0.005316422,0.004687173,0.1784062],"study_design_scores_gemma":[0.00001455633,0.00005497903,0.003757661,0.00002630876,0.00003535966,0.00002059289,0.00001736899,0.9939027,0.0001762923,0.001582125,0.0004039207,0.000008167276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3895754,0.0008770585,0.599391,0.001761105,0.0001354908,0.0003202882,0.000882154,0.001542649,0.005514825],"genre_scores_gemma":[0.9060355,0.0002235982,0.08997956,0.0002202368,0.00008477439,0.0002663616,0.001032972,0.00008486256,0.002072173],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01005649,"threshold_uncertainty_score":0.031416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0181849598262246,"score_gpt":0.2602963681174021,"score_spread":0.2421114082911776,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}