{"id":"W4405491508","doi":"10.1109/me61309.2024.10789720","title":"Body Performance Analysis with Machine Learning and ANOVA Methods","year":2024,"lang":"en","type":"article","venue":"","topic":"Body Composition Measurement Techniques","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning; Analysis of variance","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01049027,0.00235149,0.002480446,0.005745219,0.0006000312,0.001517351,0.001752017,0.0009423834,0.005384902],"category_scores_gemma":[0.0259086,0.0004536908,0.003641368,0.005054423,0.000873413,0.001083339,0.001359612,0.002698653,0.001575698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000562564,"about_ca_system_score_gemma":0.001103548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002233379,"about_ca_topic_score_gemma":0.001638078,"domain_scores_codex":[0.9887178,0.004567205,0.001304676,0.001898638,0.003030826,0.0004808434],"domain_scores_gemma":[0.9782551,0.01595837,0.001700852,0.002078631,0.001861879,0.0001451059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003172191,0.003316816,0.09141008,0.003490011,0.005137979,0.0006443199,0.001867446,0.05220545,0.02569305,0.009630886,0.0109419,0.7924898],"study_design_scores_gemma":[0.0002636093,0.01323785,0.2854344,0.0006897377,0.001914724,0.0009416037,0.002435729,0.5873668,0.04049994,0.01627551,0.05042461,0.0005155915],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.141496,0.001283538,0.8371613,0.0001840216,0.0006657886,0.003126367,0.005952132,0.004820202,0.005310691],"genre_scores_gemma":[0.4156189,0.0006474897,0.5633948,0.0001302951,0.0002375192,0.01032169,0.004894802,0.000760984,0.003993507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01049027,"threshold_uncertainty_score":0.05547851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02001873413872875,"score_gpt":0.3553912062292723,"score_spread":0.3353724720905435,"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."}}