{"id":"W3194630535","doi":"10.47206/ijsc.v1i1.81","title":"Resistance Training Recommendations to Maximize Muscle Hypertrophy in an Athletic Population: Position Stand of the IUSCA","year":2021,"lang":"en","type":"article","venue":"International Journal of Strength and Conditioning","topic":"Sports Performance and Training","field":"Medicine","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Muscle hypertrophy; Athletes; Context (archaeology); Resistance training; Muscle mass; Medicine; Population; Muscle strength; Position (finance); Skeletal muscle; Physical medicine and rehabilitation; Physical therapy; Cardiology; Internal medicine; Business; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001384221,0.00005771367,0.0001411792,0.0001419886,0.00006274513,0.00003165762,0.00006333234,0.00002655633,0.0001013001],"category_scores_gemma":[0.00006324323,0.0000483781,0.0000507047,0.0001431053,0.00002312157,0.0002505279,0.00001547842,0.0001407858,2.78945e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005644639,"about_ca_system_score_gemma":0.0001138195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007318449,"about_ca_topic_score_gemma":0.00005465941,"domain_scores_codex":[0.9991846,0.00001732355,0.0003750972,0.00008579978,0.0002597943,0.00007739748],"domain_scores_gemma":[0.9992986,0.00003406136,0.0001967616,0.00006787667,0.0003418572,0.00006085292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001363464,0.0008079009,0.7653808,0.000130132,0.0004354079,0.0009961007,0.01777977,0.00203179,0.02378581,0.01131448,0.0005016232,0.1754727],"study_design_scores_gemma":[0.001596794,0.0001152172,0.9899672,0.001309832,0.00004377747,0.0003764814,0.003355328,0.0001656279,0.001243999,0.0007081451,0.001049038,0.00006854243],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951439,0.0001750154,0.000122516,0.003653757,0.0002917025,0.00004378595,0.00001703789,0.000003238847,0.0005490643],"genre_scores_gemma":[0.9961772,0.00005913944,0.003081554,0.0003898386,0.0001704884,0.000002051303,0.00004789417,0.00000570359,0.00006614319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2245864,"threshold_uncertainty_score":0.1972802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02110525409574356,"score_gpt":0.2949676307897702,"score_spread":0.2738623766940266,"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."}}