{"id":"W2739226546","doi":"10.1080/00336297.2017.1333438","title":"Compromising Talent: Issues in Identifying and Selecting Talent in Sport","year":2017,"lang":"en","type":"article","venue":"Quest","topic":"Sports Performance and Training","field":"Medicine","cited_by":218,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; York University","funders":"","keywords":"Talent development; Athletes; Psychology; Competition (biology); Selection (genetic algorithm); Field (mathematics); Work (physics); Applied psychology; Computer science; Engineering; 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":[0.02215929,0.0006863009,0.001638184,0.004952324,0.002162131,0.006483509,0.002243228,0.00291799,0.002444632],"category_scores_gemma":[0.04562286,0.0002905911,0.0005746747,0.003828041,0.008439963,0.005969557,0.003694188,0.002959191,0.0008031972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003156804,"about_ca_system_score_gemma":0.005937221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007643444,"about_ca_topic_score_gemma":0.01118059,"domain_scores_codex":[0.9859477,0.007618554,0.00112818,0.00109417,0.003636915,0.0005744948],"domain_scores_gemma":[0.9595879,0.03199584,0.002665402,0.0006406321,0.003902767,0.001207403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00009771488,0.000159982,0.03372304,0.005558583,0.0001419917,0.0003209438,0.007874393,0.00102927,0.0005330815,0.04959936,0.008572116,0.8923895],"study_design_scores_gemma":[0.00004535401,0.001479807,0.2439779,0.04523463,0.0003853197,0.00528168,0.05745611,0.004242268,0.003110342,0.3475201,0.2907363,0.0005302767],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.05208454,0.7589707,0.03526843,0.1090883,0.002628797,0.0002320732,0.0002433011,0.0001342008,0.04134965],"genre_scores_gemma":[0.4575657,0.4878581,0.02986562,0.01577047,0.003909801,0.000355136,0.0001837783,0.00006258763,0.00442883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02215929,"threshold_uncertainty_score":0.117191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03825220290907922,"score_gpt":0.3624831223551849,"score_spread":0.3242309194461057,"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."}}