{"id":"W2063204965","doi":"10.1519/jsc.0b013e3181b4372b","title":"Use of Aggregate Fitness Indicators to Predict Transition into the National Hockey League","year":2009,"lang":"en","type":"article","venue":"The Journal of Strength and Conditioning Research","topic":"Sports Performance and Training","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Institute on Drug Abuse","keywords":"League; Percentile; Statistics; Ice hockey; Index (typography); Physical therapy; Athletes; Demography; Psychology; Mathematics; Medicine; Physical medicine and rehabilitation; Computer science","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":[0.001210107,0.000435787,0.0003796901,0.001336896,0.0002611204,0.0008413382,0.0003542862,0.000421641,0.001257891],"category_scores_gemma":[0.003694553,0.0001581111,0.0003890386,0.0004978205,0.0001701133,0.0003699214,0.0006309418,0.0005989864,0.0004413194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002744759,"about_ca_system_score_gemma":0.0003163645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01020886,"about_ca_topic_score_gemma":0.01976758,"domain_scores_codex":[0.9996181,0.00009809437,0.0000501105,0.00006280321,0.0001125477,0.00005840987],"domain_scores_gemma":[0.9983482,0.0003620117,0.0005221408,0.00009679699,0.0003289897,0.0003419402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009377028,0.00003924024,0.9975954,0.000002715665,0.00003301565,0.000008109389,0.00002028443,0.0001347588,0.00006983791,0.000008038014,0.00008967039,0.001905196],"study_design_scores_gemma":[0.000009656619,0.0001767862,0.9977462,0.000006927387,0.0000302461,0.00003044585,0.0001085056,0.001645312,0.0000889263,0.00003201167,0.0001208859,0.000004141939],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984975,0.0000943761,0.0002636009,0.00004873449,0.00001109237,0.00001433604,0.0003333505,0.00001056904,0.0007264759],"genre_scores_gemma":[0.9990396,0.00003892172,0.0001619181,0.000009057986,0.000005008013,0.000008962067,0.0005463465,0.000001786797,0.0001883519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01020886,"threshold_uncertainty_score":0.0202989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05291370982569264,"score_gpt":0.3561999525730498,"score_spread":0.3032862427473571,"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."}}