{"id":"W2066879210","doi":"10.1023/b:mark.0000012474.56171.e9","title":"An Easily Implemented Framework for Forecasting Ticket Sales to Performing Arts Events","year":2003,"lang":"en","type":"article","venue":"Marketing Letters","topic":"Art History and Market Analysis","field":"Arts and Humanities","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ticket; Entertainment; Sample (material); Marketing; Computer science; Entertainment industry; Business; Sales management; Advertising; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001137911,0.001042327,0.0009559172,0.001098366,0.000714544,0.001640389,0.001539486,0.001223852,0.006755873],"category_scores_gemma":[0.002935401,0.0005642486,0.001054448,0.0008840784,0.0002203812,0.001195985,0.000800044,0.0009407767,0.001985625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009721775,"about_ca_system_score_gemma":0.002138356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06775206,"about_ca_topic_score_gemma":0.06612992,"domain_scores_codex":[0.9996729,0.00005599645,0.00002725883,0.00009635209,0.00009526262,0.00005226232],"domain_scores_gemma":[0.9994395,0.0002133429,0.00003688251,0.00007206927,0.000183791,0.00005431195],"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":[0.0005057728,0.0006009656,0.01121644,0.0001318773,0.0003256836,0.0003027396,0.0001069198,0.5845206,0.006578811,0.008086028,0.02122019,0.3664039],"study_design_scores_gemma":[0.00003071556,0.00001734023,0.0005453001,0.000003451275,0.0000153052,0.00001563652,0.00000950963,0.9950525,0.0007892585,0.002041991,0.001471886,0.000007068245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04604451,0.0002457759,0.9160106,0.000276092,0.0001639894,0.0003189285,0.002701843,0.03125188,0.002986426],"genre_scores_gemma":[0.3496532,0.0001565503,0.6401823,0.0001348727,0.0001172129,0.000303645,0.004197538,0.0004226041,0.004832236],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06775206,"threshold_uncertainty_score":0.1347154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05752299777540908,"score_gpt":0.2726960184159097,"score_spread":0.2151730206405006,"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."}}