{"id":"W2767320787","doi":"10.1111/sms.13009","title":"Influence of population size, density, and proximity to talent clubs on the likelihood of becoming elite youth athlete","year":2017,"lang":"en","type":"article","venue":"Scandinavian Journal of Medicine and Science in Sports","topic":"Sport Psychology and Performance","field":"Psychology","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Elite; Talent development; League; Athletes; Club; Football; Elite athletes; Population; Psychology; Geography; Demographic economics; Political science; Demography; Sociology; Medicine; Physical therapy; Economics; Politics","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":[0.00327048,0.0000917622,0.0002949929,0.0002262423,0.0001997608,0.00001026507,0.000319928,0.00005188629,0.00004172924],"category_scores_gemma":[0.0005108282,0.00005580626,0.0000234397,0.0001927741,0.00101439,0.0002558741,0.00004949072,0.0002230979,3.309369e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001496311,"about_ca_system_score_gemma":0.00003574889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002403214,"about_ca_topic_score_gemma":0.00003621958,"domain_scores_codex":[0.9987115,0.00002901318,0.0005037953,0.0001821978,0.0003831912,0.0001902948],"domain_scores_gemma":[0.9985391,0.0000768015,0.0007680572,0.000325996,0.0001410029,0.0001490805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002093457,0.00003232695,0.981508,0.00001088363,0.000003609976,0.0000338005,0.007890081,0.000009709665,0.0005758562,0.0001822541,0.00002749565,0.009516685],"study_design_scores_gemma":[0.0006341491,0.0005079872,0.9950523,0.001049104,0.00001762827,0.0001272327,0.001477171,0.000004410188,0.0001435013,0.0009174045,0.00001533142,0.00005381344],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967887,0.0001419142,0.000003474999,0.001836926,0.0004075978,0.0001407086,0.000001478034,0.000001266634,0.0006778819],"genre_scores_gemma":[0.9993142,0.0001090484,0.00004774428,0.000423962,0.00007518459,9.701445e-7,2.001374e-7,0.000003076998,0.0000256318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01354432,"threshold_uncertainty_score":0.3737564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03683256958841995,"score_gpt":0.3456626119639533,"score_spread":0.3088300423755334,"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."}}