{"id":"W4293227217","doi":"10.1287/mnsc.2022.4307","title":"Revenue-Sharing Allocation Strategies for Two-Sided Media Platforms: Pro-Rata vs. User-Centric","year":2022,"lang":"en","type":"article","venue":"Management Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Cambridge; Strong; Università degli Studi di Cagliari","keywords":"Revenue; Computer science; Knapsack problem; Profit (economics); Set (abstract data type); Operations research; Economics; Microeconomics; Algorithm; 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":[0.003025091,0.001831444,0.001793444,0.0009869228,0.0009539833,0.00321884,0.003234038,0.002064717,0.007091552],"category_scores_gemma":[0.009210096,0.0008196364,0.001153494,0.0009746909,0.001465388,0.003337313,0.002674693,0.0022851,0.0008264155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002554908,"about_ca_system_score_gemma":0.001916865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002808577,"about_ca_topic_score_gemma":0.002173214,"domain_scores_codex":[0.9979727,0.0007600372,0.00007928973,0.0003511148,0.0003244474,0.0005125106],"domain_scores_gemma":[0.9944813,0.00324976,0.0006390738,0.000430254,0.0004104632,0.0007891539],"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":[0.0006076363,0.0004840574,0.000916497,0.0002170257,0.0001046437,0.0005240731,0.000189204,0.8350601,0.005051294,0.1125565,0.004378171,0.03991069],"study_design_scores_gemma":[0.00004134227,0.0000951602,0.0001254735,0.00001613787,0.00001408756,0.00008979256,0.00006490649,0.978588,0.0005673538,0.01949206,0.000889004,0.00001673426],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1764975,0.0009804581,0.7864158,0.001559192,0.0002251004,0.0008559861,0.0004269615,0.0004959731,0.03254308],"genre_scores_gemma":[0.9368451,0.0003425206,0.05715628,0.000165167,0.00008244887,0.0002197538,0.00009806792,0.00008238984,0.005008375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007091552,"threshold_uncertainty_score":0.0237236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03827223262575408,"score_gpt":0.2722747049929611,"score_spread":0.2340024723672071,"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."}}