{"id":"W2942686481","doi":"10.1111/poms.13035","title":"Monetization on Mobile Platforms: Balancing in‐App Advertising and User Base Growth","year":2019,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Monetization; Advertising; Revenue; Computer science; Android (operating system); App store; Revenue sharing; Payment; Online advertising; Order (exchange); Contextual advertising; Search advertising; Planner; Business; Mobile apps; World Wide Web; The Internet; Economics; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001656181,0.0001047476,0.00009514424,0.0002539651,0.0001265115,0.0005319675,0.00003899638,0.00002362128,0.00005022018],"category_scores_gemma":[0.00001681954,0.00009684333,0.00001273558,0.0001803867,0.00001392092,0.003419967,0.00007734412,0.00005191289,0.0001221065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003047206,"about_ca_system_score_gemma":0.000002488534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006824442,"about_ca_topic_score_gemma":0.0001263747,"domain_scores_codex":[0.9993253,6.213606e-7,0.0001796761,0.0002926295,0.0000736063,0.0001281324],"domain_scores_gemma":[0.9997998,0.000003704067,0.0000364785,0.0001195849,0.00003089507,0.000009554509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001244194,0.0003737205,0.1059547,0.0009218756,0.00006689571,0.000005976547,0.0003508422,0.1252024,0.0003131854,0.7094832,0.002717085,0.0544857],"study_design_scores_gemma":[0.006436466,0.0003041628,0.3650499,0.001262274,0.0002058164,0.00002170391,0.0200413,0.485107,0.001011822,0.03132586,0.08633761,0.002896016],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821584,0.00003300066,0.0002081348,0.000256558,0.0003152105,0.0005938042,4.71907e-7,0.00005136218,0.01638305],"genre_scores_gemma":[0.9970991,0.0001081387,0.0002911745,0.0006838159,0.0001507743,0.00004398048,0.00003261644,0.00001272096,0.001577665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6781573,"threshold_uncertainty_score":0.5129775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005815103460808936,"score_gpt":0.1814704592630809,"score_spread":0.1756553558022719,"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."}}