{"id":"W2991469626","doi":"10.2139/ssrn.3476296","title":"Optimal Subscription Planning for Digital Goods","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Renting; Cardinality (data modeling); Revenue; Set (abstract data type); Value (mathematics); Computer science; Service (business); Digital goods; Advertising; Business; Database; World Wide Web; Marketing; Finance; Engineering","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":[0.002062324,0.0009755461,0.002448994,0.002055646,0.000955233,0.004342328,0.001732028,0.003329535,0.02640424],"category_scores_gemma":[0.01111732,0.001615957,0.001209392,0.002601872,0.00136883,0.004223205,0.001636528,0.002207099,0.001611614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003009904,"about_ca_system_score_gemma":0.002641639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008404692,"about_ca_topic_score_gemma":0.006853206,"domain_scores_codex":[0.9988785,0.0004567591,0.0000507909,0.0001707116,0.0001370831,0.0003061276],"domain_scores_gemma":[0.9936358,0.005042451,0.0002524331,0.0002052763,0.000294627,0.0005694512],"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":[0.0009697356,0.0004670293,0.001199724,0.0004359927,0.0000825943,0.000359657,0.0002792701,0.7933903,0.001672177,0.1076844,0.01441638,0.07904286],"study_design_scores_gemma":[0.0001137082,0.0001223189,0.0004336292,0.00004439867,0.00004011369,0.00004526542,0.0001944679,0.9218467,0.000616316,0.07416741,0.002350223,0.00002551097],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3302108,0.002413033,0.541621,0.005899785,0.000404619,0.001162717,0.001489213,0.001403032,0.1153959],"genre_scores_gemma":[0.9067008,0.001008979,0.05973499,0.0002291422,0.0001761136,0.0002545008,0.0004574824,0.0002296136,0.03120849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02640424,"threshold_uncertainty_score":0.08833098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0112459523979078,"score_gpt":0.2059353335857991,"score_spread":0.1946893811878913,"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."}}