{"id":"W4377093594","doi":"10.1287/opre.2023.2468","title":"Optimal Subscription Planning for Digital Goods","year":2023,"lang":"en","type":"article","venue":"Operations Research","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Revenue; Set (abstract data type); Operations research; Tier 2 network; Microeconomics; Business; Mathematical optimization; Economics; Computer network; 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":[0.001476143,0.0009967914,0.001593366,0.0009572387,0.000687646,0.002445511,0.001222844,0.002130846,0.01880763],"category_scores_gemma":[0.006058794,0.0009721729,0.0009360901,0.001862606,0.001007599,0.00315159,0.001229678,0.001791992,0.0009841467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002781054,"about_ca_system_score_gemma":0.001605519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006551854,"about_ca_topic_score_gemma":0.006040481,"domain_scores_codex":[0.9990628,0.0003849972,0.00004258575,0.0001819637,0.0001091784,0.0002184148],"domain_scores_gemma":[0.9966462,0.002654201,0.000130807,0.000130738,0.0001908134,0.0002471809],"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":[0.0006388788,0.0004150973,0.001270897,0.0004751336,0.0001669571,0.0003593344,0.0002861197,0.6842954,0.002108253,0.2108947,0.01356543,0.0855238],"study_design_scores_gemma":[0.0001026725,0.0001121847,0.000536171,0.00004569979,0.00004875158,0.00007361753,0.0001725906,0.8676136,0.0006087897,0.1243034,0.006351556,0.0000309461],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1592624,0.005531975,0.7314705,0.003915279,0.0003807664,0.0008787055,0.001234762,0.0008609885,0.09646463],"genre_scores_gemma":[0.8737565,0.001666809,0.1032145,0.0003549959,0.000105403,0.000225713,0.0004503243,0.0001651892,0.02006052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01880763,"threshold_uncertainty_score":0.06291777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1724809458499401,"score_gpt":0.3662416084710237,"score_spread":0.1937606626210836,"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."}}