{"id":"W2981217933","doi":"10.3390/data4040141","title":"Capacity Allocation of Game Tickets Using Dynamic Pricing","year":2019,"lang":"en","type":"article","venue":"Data","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Queen's University","keywords":"Ticket; Revenue; Dynamic pricing; Football; Business; Advertising; Club; Sequential game; Microeconomics; Game theory; Marketing; Economics; Computer science; Computer security","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001531568,0.001010975,0.001402241,0.00135955,0.000464006,0.002427805,0.001931891,0.00100043,0.005360196],"category_scores_gemma":[0.00706105,0.0007350679,0.0009374464,0.001426197,0.001000798,0.002492184,0.001228912,0.001647046,0.0003704609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002344325,"about_ca_system_score_gemma":0.001324629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005250761,"about_ca_topic_score_gemma":0.00381508,"domain_scores_codex":[0.9986851,0.0005934132,0.00004164369,0.000202243,0.0002208283,0.000256756],"domain_scores_gemma":[0.9974501,0.001834977,0.0001943422,0.0001355866,0.0001894913,0.0001955633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005707253,0.00008994787,0.0004020919,0.00005452275,0.00002173556,0.00004276195,0.0000317515,0.9520308,0.0005243475,0.03216699,0.0006039661,0.01397401],"study_design_scores_gemma":[0.000005913766,0.0000238377,0.000132165,0.000005786285,0.000005601124,0.00001448137,0.0000163454,0.9870576,0.0001476176,0.01213885,0.0004433923,0.000008313526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1030982,0.000678831,0.872406,0.0004966786,0.0001069206,0.0002356538,0.0002318002,0.0002545504,0.02249128],"genre_scores_gemma":[0.9564882,0.0003314893,0.03921275,0.00005897248,0.0000542729,0.0001093167,0.0001316013,0.00007608622,0.003537447],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005360196,"threshold_uncertainty_score":0.01793158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.108246630463196,"score_gpt":0.2626288117917647,"score_spread":0.1543821813285687,"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."}}