{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001500446,0.000152886,0.0003380261,0.0002736599,0.0006733215,0.00001289563,0.0002327073,0.00004771922,0.0005960605],"category_scores_gemma":[0.000163852,0.000104161,0.00002901138,0.0001473455,0.02987875,0.0002970599,0.0001000746,0.000196215,0.00001801753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000409334,"about_ca_system_score_gemma":0.00006575338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001259278,"about_ca_topic_score_gemma":0.005567732,"domain_scores_codex":[0.9984379,0.00001933085,0.0003647022,0.0003538128,0.0004090015,0.000415188],"domain_scores_gemma":[0.9994218,0.000045057,0.0001018488,0.0002418402,0.0001112124,0.00007824675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001126988,0.0002927812,0.5000957,0.0002126218,0.000002426581,0.00007267993,0.3260786,0.0002218385,0.0001474851,0.1220204,0.006231801,0.04451102],"study_design_scores_gemma":[0.002538774,0.0009442638,0.4389324,0.002720738,0.0002557182,0.00006894769,0.2330634,0.112133,0.0002658259,0.1995951,0.008336745,0.001145109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767514,0.00007752466,0.0003004275,0.00422368,0.001553668,0.0001868477,0.000001916899,0.0000882016,0.01681637],"genre_scores_gemma":[0.9970806,0.0001179064,0.0002380138,0.0003573933,0.0002987625,0.00002157685,0.000003499275,0.000006354458,0.001875947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1119112,"threshold_uncertainty_score":0.9727613,"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."}}