{"id":"W2011197370","doi":"10.1519/r-15304.1","title":"Prediction of One Repetition Maximum Strength From Multiple Repetition Maximum Testing and Anthropometry","year":2006,"lang":"en","type":"article","venue":"The Journal of Strength and Conditioning Research","topic":"Sports Performance and Training","field":"Medicine","cited_by":315,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Society for Exercise Physiology","funders":"","keywords":"Bench press; One-repetition maximum; Mathematics; Anthropometry; Linear regression; Leg press; Repetition (rhetorical device); Regression analysis; Nonlinear regression; Statistics; Resistance training; Animal science; Medicine; Physical therapy; Internal medicine","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":[0.001093813,0.00074828,0.0003711925,0.0004957481,0.00008703092,0.0002577812,0.0002416119,0.0003541806,0.00116408],"category_scores_gemma":[0.004731377,0.0002131733,0.0002368221,0.0002381227,0.0001490116,0.0002505692,0.0001965592,0.0004175852,0.0007311848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007943662,"about_ca_system_score_gemma":0.0001149228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001851434,"about_ca_topic_score_gemma":0.002646755,"domain_scores_codex":[0.9995393,0.0001868382,0.00002836381,0.00008932969,0.0001233946,0.00003276061],"domain_scores_gemma":[0.9984793,0.0007996945,0.0003942751,0.00005628552,0.0002050067,0.00006556991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004410907,0.0001988739,0.9384703,0.0000982538,0.0001496966,0.0001889394,0.0001302559,0.004526404,0.008400884,0.00004812281,0.0004583749,0.04688879],"study_design_scores_gemma":[0.00001342798,0.000482648,0.9901066,0.00001136843,0.00003139159,0.0002668242,0.00003644726,0.007394888,0.001322337,0.0000475177,0.000277561,0.00000888494],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911247,0.0004468143,0.007100382,0.00006025835,0.00002530914,0.00003285416,0.0002519491,0.00008318094,0.0008745309],"genre_scores_gemma":[0.9960408,0.0001613363,0.00272296,0.00002845687,0.00002746881,0.00002711792,0.0003055407,0.00001470357,0.0006715773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001851434,"threshold_uncertainty_score":0.00578475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05919349322270426,"score_gpt":0.314504001753458,"score_spread":0.2553105085307537,"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."}}