{"id":"W2167612934","doi":"10.1287/inte.1030.0049","title":"Preferred Scenarios in the Sport of Curling","year":2004,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Federated Co-operatives (Canada)","funders":"","keywords":"Championship; Curling; Shot (pellet); World championship; Point (geometry); Class (philosophy); Advertising; Team sport; Tipping point (physics); Marketing; Psychology; Computer science; Engineering; Mathematics; Artificial intelligence; Athletes; Business","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":[0.005093805,0.0005726828,0.0003639034,0.001491502,0.001621219,0.004615413,0.0007466872,0.00213797,0.00738706],"category_scores_gemma":[0.01985732,0.0003045099,0.0004434989,0.0007687393,0.001827677,0.003107524,0.001846812,0.001318722,0.0009038579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001417693,"about_ca_system_score_gemma":0.0008598181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007892395,"about_ca_topic_score_gemma":0.01966125,"domain_scores_codex":[0.9949175,0.003247012,0.0001880903,0.0003736432,0.0008441697,0.0004295867],"domain_scores_gemma":[0.9936756,0.00329959,0.0007044263,0.0004152466,0.0008616197,0.001043412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003435234,0.001009709,0.3276607,0.001109946,0.000864516,0.005039869,0.04681027,0.04380177,0.006248222,0.4302115,0.02683998,0.1069684],"study_design_scores_gemma":[0.0004335805,0.001115212,0.1273179,0.0007039062,0.000217186,0.004997499,0.09788133,0.0973637,0.002151889,0.5465045,0.120809,0.0005043277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8841854,0.0006503194,0.0226652,0.003065486,0.00007988077,0.0001227944,0.0007234594,0.00007046744,0.08843698],"genre_scores_gemma":[0.9950283,0.0001372137,0.003075415,0.000170235,0.00001111199,0.00003392846,0.0002315633,0.00001212422,0.001300022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007892395,"threshold_uncertainty_score":0.02693892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03536256942786613,"score_gpt":0.2321553533887104,"score_spread":0.1967927839608442,"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."}}