{"id":"W2897360389","doi":"10.1057/s41272-018-00170-6","title":"Distribution-free bounds for the expected marginal seat revenue heuristic with dependent demands","year":2018,"lang":"en","type":"article","venue":"Journal of Revenue and Pricing Management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Revenue management; Yield management; Heuristic; Revenue; Marginal revenue; Econometrics; Business process management; Computer science; Distribution (mathematics); Economics; Operations research; E-commerce; Mathematical optimization; Operations management; Mathematics; Finance","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":[0.00982625,0.003105137,0.003979918,0.003060882,0.001485998,0.005797278,0.008212652,0.003595495,0.02037409],"category_scores_gemma":[0.03761694,0.00197754,0.00246649,0.003522888,0.002793743,0.00915709,0.003856189,0.007639816,0.002243831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006454374,"about_ca_system_score_gemma":0.005572012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005019806,"about_ca_topic_score_gemma":0.006480669,"domain_scores_codex":[0.9947075,0.002359645,0.0001435362,0.0004729297,0.0009664439,0.001350016],"domain_scores_gemma":[0.9535284,0.04037277,0.000933653,0.002195761,0.001490524,0.001478792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001297305,0.0007451558,0.0008458924,0.0004576338,0.0001683535,0.0001075737,0.0002006631,0.8607236,0.001030354,0.07580411,0.0124922,0.04612711],"study_design_scores_gemma":[0.00008925527,0.0000781426,0.0001682132,0.0000568731,0.0000393985,0.00003455857,0.00003655861,0.958964,0.0003721049,0.03948582,0.0006562566,0.00001879573],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0766501,0.003959025,0.8565787,0.003772024,0.0005368904,0.0004878769,0.001256514,0.001889357,0.05486955],"genre_scores_gemma":[0.723263,0.001454796,0.2552461,0.001164511,0.0005882163,0.0006361937,0.001636304,0.001567804,0.01444308],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02037409,"threshold_uncertainty_score":0.06815809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01220054446158747,"score_gpt":0.2180825378675072,"score_spread":0.2058819934059197,"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."}}