{"id":"W2596566402","doi":"","title":"The birthplace effect in national hockey league draftees: Exploring between city variability trends in athlete development","year":2016,"lang":"en","type":"article","venue":"","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Ontario Tech University","funders":"","keywords":"League; Population; Geography; Demography; Athletes; Statistics; Mathematics; Sociology; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003361724,0.0003231541,0.0004533092,0.002620406,0.0008445716,0.001136368,0.001455773,0.0004254029,0.001722499],"category_scores_gemma":[0.01197593,0.0003393811,0.001236498,0.003434227,0.0009747461,0.0007433111,0.001429176,0.0008781106,0.0001997535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002269557,"about_ca_system_score_gemma":0.002455493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4292029,"about_ca_topic_score_gemma":0.4769163,"domain_scores_codex":[0.9971763,0.0007797938,0.0002353071,0.0007685871,0.0006053497,0.0004347883],"domain_scores_gemma":[0.992139,0.002696927,0.002270006,0.0008549551,0.001491416,0.0005477217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007364583,0.00001858159,0.9970157,0.0000185067,0.000168371,0.00002590029,0.0006026258,0.0001375546,0.00006304298,0.0001405241,0.0002192607,0.001516293],"study_design_scores_gemma":[0.000002476664,0.00003759123,0.998105,0.00001230878,0.00004580141,0.00001882666,0.0009254712,0.0003912055,0.00006659213,0.00003953784,0.000350237,0.000004862025],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995846,0.0002660273,0.0008160481,0.0000815168,0.00001479919,0.00003490617,0.002025828,0.00001105733,0.0009038171],"genre_scores_gemma":[0.9974231,0.00009696014,0.0005306806,0.00002368048,0.000007542536,0.00005752526,0.001419213,0.00001150641,0.0004299319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4292029,"threshold_uncertainty_score":0.8534093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0805276511501913,"score_gpt":0.2481963312239726,"score_spread":0.1676686800737813,"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."}}