{"id":"W2525145585","doi":"","title":"The impact of power distribution in actor training","year":2015,"lang":"en","type":"article","venue":"Intersections Canadian Journal of Music","topic":"Human Motion and Animation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Power (physics); Distribution (mathematics); Psychology; Computer science; Mathematics education; Mathematics; Geography; Physics; Meteorology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001946444,0.00004247111,0.00006745521,0.0001651011,0.00003482993,0.00002410297,0.00006446978,0.00002472016,0.0001003566],"category_scores_gemma":[0.00008709633,0.00003207122,0.00006938184,0.0001502675,0.00002590038,0.0001174508,0.000001216998,0.0001425376,0.000004268997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004362432,"about_ca_system_score_gemma":0.0002428653,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001983927,"about_ca_topic_score_gemma":0.05459667,"domain_scores_codex":[0.9996024,0.00001957051,0.0002007935,0.00002136191,0.00005186233,0.0001039832],"domain_scores_gemma":[0.9996427,0.00001622678,0.00004879593,0.00004379527,0.00008666194,0.0001618096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000150804,0.0001195245,0.04075127,0.00004169824,0.000816542,0.0001883775,0.2271228,0.3692881,0.01089773,0.005436768,0.265979,0.07920733],"study_design_scores_gemma":[0.003001948,0.001408107,0.8609104,0.0006149224,0.00004791045,0.0009418582,0.06214119,0.03206764,0.0006257291,0.002814787,0.03486273,0.0005628307],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956598,0.00005924321,0.001993768,0.00004792877,0.0006079631,0.00002464649,0.00001480269,0.000004928834,0.001586939],"genre_scores_gemma":[0.9999061,0.000001831094,0.00001086888,0.000003804752,0.00005430209,5.033376e-7,0.000001955312,0.000005221698,0.00001537084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8201591,"threshold_uncertainty_score":0.9626545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04215675415195651,"score_gpt":0.2504001723271708,"score_spread":0.2082434181752142,"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."}}