{"id":"W3122813159","doi":"","title":"Endogenous Differentiation of Information Goods Under Uncertainty","year":2007,"lang":"en","type":"article","venue":"Deep Blue (University of Michigan)","topic":"Business Strategy and Innovation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Johns Hopkins University; National Science Foundation","keywords":"Profit (economics); Incentive; Microeconomics; Profitability index; Product proliferation; Industrial organization; Information good; Competition (biology); Economics; Business; Learning effect; New product development; Marketing; The Internet; Computer science","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":[0.0002092143,0.00007927815,0.0001247858,0.0003155619,0.0001204759,0.00001793994,0.00014283,0.00007966773,0.000129434],"category_scores_gemma":[0.00001382539,0.00009422519,0.00004804016,0.0005437202,0.00005996764,0.001582259,0.00005247925,0.00006627401,0.00003681778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001582624,"about_ca_system_score_gemma":0.00001449908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007008468,"about_ca_topic_score_gemma":0.005275313,"domain_scores_codex":[0.9994681,0.000003981932,0.000169382,0.00007782297,0.0001555953,0.0001251136],"domain_scores_gemma":[0.99923,0.00001604042,0.000364482,0.0001121603,0.0002713079,0.000006054168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001234258,0.0007009463,0.01093813,0.001706819,0.0003672803,0.00001248117,0.02824022,0.02302709,0.07054337,0.7960297,0.0001392509,0.06706044],"study_design_scores_gemma":[0.006319808,0.0001018457,0.705312,0.00021101,0.0005098237,0.000009504437,0.1985287,0.04958097,0.006008653,0.01336679,0.01894387,0.001107028],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.91264,0.00001039257,0.08001754,0.0001135062,0.0001307734,0.00009449189,0.0000029434,0.00003343471,0.006956972],"genre_scores_gemma":[0.9992857,0.000004754432,0.0003007833,0.0001446819,0.00006187239,5.229966e-8,0.0001734602,0.000004036531,0.00002468337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7826629,"threshold_uncertainty_score":0.3842392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01630074703858415,"score_gpt":0.1803268884008331,"score_spread":0.1640261413622489,"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."}}