{"id":"W4389982647","doi":"10.48550/arxiv.2312.10205","title":"Pay to (Not) Play: Monetizing Impatience in Mobile Games","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alberta Machine Intelligence Institute; Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency; Canadian Institute for Advanced Research","keywords":"Monetization; Revenue; Gratification; Revenue model; Computer science; Microeconomics; Advertising; Marketing; Business; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001940947,0.0002729563,0.000326889,0.0005814175,0.00007630085,0.0005400556,0.0006155421,0.0001644704,0.00005286799],"category_scores_gemma":[0.00004504703,0.0002798667,0.0001311595,0.0005687276,0.00003957805,0.002014776,0.001844267,0.0003260999,0.00160888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001586858,"about_ca_system_score_gemma":0.00004196908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001794516,"about_ca_topic_score_gemma":0.001078747,"domain_scores_codex":[0.9985417,0.000001558735,0.0002454099,0.0007480445,0.0000538166,0.0004094884],"domain_scores_gemma":[0.9992247,0.0000414734,0.0002037654,0.0004415206,0.00005319971,0.00003530235],"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":[0.00009612165,0.00008435707,0.05113542,0.0002395275,0.00004097006,0.0003034876,0.0001629647,0.9108998,0.00001319296,0.03213517,0.001566804,0.003322203],"study_design_scores_gemma":[0.00193354,0.00009527467,0.1081146,0.001086839,0.0001610253,0.000002122676,0.006432165,0.5659258,0.0000666643,0.2798885,0.03279832,0.003495232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907015,0.000007533912,0.0004653512,0.00004485345,0.0006223466,0.0004142814,0.00001264927,0.0001900064,0.007541487],"genre_scores_gemma":[0.9973391,0.00004428855,0.00002893149,0.0004207636,0.0002303358,0.000005114432,0.00004868257,0.00003927428,0.001843532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.344974,"threshold_uncertainty_score":0.9999654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07593730085406457,"score_gpt":0.1766826853866585,"score_spread":0.1007453845325939,"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."}}