{"id":"W3126300937","doi":"10.1123/smej.2019-0070","title":"Sport Analytics Education for Future Executives, Managers, and Nontechnical Personnel","year":2021,"lang":"en","type":"article","venue":"Sport Management Education Journal","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"Analytics; Business analytics; Curriculum; Experiential learning; Knowledge management; Sport management; Business; Public relations; Psychology; Computer science; Marketing; Business analysis; Data science; Business model; Pedagogy; Political 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005489644,0.0001749488,0.000314142,0.0003729247,0.000291035,0.0002315015,0.0001744455,0.00008162408,0.000551902],"category_scores_gemma":[0.00001206761,0.000199299,0.0001554677,0.000328577,0.00003797806,0.0003173121,0.00004589362,0.0001983986,0.0000270223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001391207,"about_ca_system_score_gemma":0.0002504307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000152628,"about_ca_topic_score_gemma":0.000007795458,"domain_scores_codex":[0.9986033,0.00000215076,0.0006442847,0.0004018621,0.00007969378,0.0002687038],"domain_scores_gemma":[0.998806,0.000004234095,0.0004858054,0.0003159173,0.0001686795,0.0002193454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002457938,0.0005168617,0.1460217,0.0001658666,0.0001862188,0.00001713065,0.0005074143,0.00005587802,6.642318e-7,0.7937075,0.03466431,0.02413193],"study_design_scores_gemma":[0.0003010836,0.00002833113,0.1147647,0.00005248419,0.00007150236,0.0001106002,0.00812001,0.0005272846,0.000003621732,0.0103918,0.8653591,0.0002694566],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6825158,0.02751972,0.02990104,0.01947987,0.01528798,0.001644095,0.00009408854,0.0001089026,0.2234485],"genre_scores_gemma":[0.9385454,0.00919337,0.01327189,0.00190516,0.001912651,0.00005460241,0.0002175725,0.00003941292,0.03485994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8306948,"threshold_uncertainty_score":0.8127176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517342339998473,"score_gpt":0.2425738302162626,"score_spread":0.2274004068162779,"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."}}