{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003178577,0.00005378248,0.0001671698,0.00008154857,0.00001666283,0.00001666179,0.0002761798,0.00003248675,0.0003295132],"category_scores_gemma":[0.00002125616,0.00006067533,0.00001909537,0.0001126723,0.00001730084,0.0002595905,0.00009766228,0.00005134892,0.0001911405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003085219,"about_ca_system_score_gemma":0.0000112754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005175218,"about_ca_topic_score_gemma":0.00002958174,"domain_scores_codex":[0.9993725,0.000001725062,0.0002862477,0.000211449,0.00002383969,0.0001042748],"domain_scores_gemma":[0.9990034,0.000009143015,0.0002283651,0.0007229612,0.00001627145,0.00001989837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000152863,0.0001501955,0.9069393,0.0002917722,0.0001155089,0.000001416351,0.0006447331,0.008844257,0.001577762,0.07802104,0.0005710817,0.00282762],"study_design_scores_gemma":[0.0001288745,0.00001162672,0.07843235,0.00001939204,0.000004898983,0.000001381724,0.00001388175,0.9097524,0.00005357524,0.0009020412,0.01058182,0.00009771183],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920582,0.0002128192,0.004772801,0.00004933548,0.0002071063,0.000074398,0.0004595315,0.000006076961,0.002159687],"genre_scores_gemma":[0.9986729,0.00007825108,0.0007367142,0.00004184639,0.00001974788,3.113249e-7,0.0002574835,0.000007800635,0.0001849341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9009082,"threshold_uncertainty_score":0.3607939,"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."}}