{"id":"W4379930237","doi":"10.36950/2023.1ciss008","title":"Talent inclusion and genetic testing in sport: A practitioner’s guide","year":2023,"lang":"en","type":"article","venue":"Current Issues in Sport Science (CISS)","topic":"Genetics and Physical Performance","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Genetic testing; Inclusion (mineral); Athletes; Appeal; Promotion (chess); Identification (biology); Selection (genetic algorithm); Best practice; Psychology; Political science; Biology; Genetics; Computer science; Medicine; Social psychology","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":[0.0005159182,0.0001447458,0.0001533379,0.0001835977,0.0001910489,0.00003678537,0.0003162062,0.00005244977,0.000006887461],"category_scores_gemma":[0.0001032028,0.0001394084,0.00002345153,0.0009907403,0.0002664931,0.00001943281,0.0009281061,0.0001279028,0.00001977053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002992814,"about_ca_system_score_gemma":0.0001275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007347975,"about_ca_topic_score_gemma":0.00005642708,"domain_scores_codex":[0.9984102,0.000006682023,0.000314177,0.0005381603,0.0003398852,0.0003909222],"domain_scores_gemma":[0.9994084,0.000006727736,0.00009406574,0.0003003769,0.00007958552,0.0001108766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002187034,0.0001794225,0.7583834,0.00006973641,0.000001831029,0.00004144711,0.000511918,0.00284575,0.1927585,0.000127948,0.0005619413,0.04449622],"study_design_scores_gemma":[0.0003544046,0.0001636048,0.8869597,0.000164439,0.000004512328,0.0000157858,0.0001009501,0.00801677,0.02049645,0.0006376536,0.0827435,0.0003422762],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972794,0.00154741,0.00001784053,0.0001510941,0.0002827539,0.0001969714,0.000003971086,0.00001465568,0.000505923],"genre_scores_gemma":[0.9970092,0.001765522,0.0007897452,0.00004046794,0.0001600709,0.00002410168,0.00004078062,0.00001098053,0.0001591518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1722621,"threshold_uncertainty_score":0.5684907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02458726316099736,"score_gpt":0.3403897877288634,"score_spread":0.3158025245678661,"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."}}