{"id":"W3125420432","doi":"","title":"Can Brand Extension Signal Product Quality","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Product (mathematics); Argument (complex analysis); Quality (philosophy); Brand extension; Extension (predicate logic); Pooling; Economics; Bayesian game; Microeconomics; Observability; Mathematical economics; Econometrics; Computer science; Marketing; Mathematics; Business; Brand awareness; Game theory; Repeated game","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02569822,0.0001541853,0.0002537368,0.0003070158,0.0005480484,0.0001923531,0.0004581121,0.00006105197,0.000632782],"category_scores_gemma":[0.002490148,0.0001042302,0.0001354526,0.0008903667,0.00006780178,0.0005122095,0.00008036304,0.001413423,0.0002159746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003432503,"about_ca_system_score_gemma":0.001069951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003003423,"about_ca_topic_score_gemma":0.0001652323,"domain_scores_codex":[0.9946485,0.0003950743,0.0008843787,0.000287234,0.001491112,0.002293771],"domain_scores_gemma":[0.9980361,0.000277204,0.0005351958,0.0003296142,0.0006448456,0.000176988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001537384,0.0002366088,0.05737475,0.000002628619,0.00004879269,0.000002235916,0.001359182,0.00003443571,0.01403882,0.3308593,0.00329914,0.5925903],"study_design_scores_gemma":[0.001922318,0.0002854084,0.09440997,0.00002800575,0.00002835677,0.002102649,0.01012649,0.0004807155,0.002782875,0.8545955,0.03253994,0.0006978074],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9771264,0.001128993,0.01263732,0.003345413,0.0008679722,0.0001205901,0.000002350608,0.00003557405,0.00473543],"genre_scores_gemma":[0.9916371,0.00007432436,0.0002054575,0.0004701533,0.001005936,0.000001627392,0.000002008217,0.00001382347,0.006589639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5918925,"threshold_uncertainty_score":0.8906543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.105745211652882,"score_gpt":0.3825940780773715,"score_spread":0.2768488664244895,"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."}}