{"id":"W3122456732","doi":"","title":"Inferring Market Structure from Customer Response to Competing and Complementary Products","year":2001,"lang":"en","type":"article","venue":"","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Market structure; Market analysis; Market share analysis; Set (abstract data type); Market research; Market microstructure; Market segmentation; Industrial organization; Marketing; Business; Data science; Computer science; Order (exchange)","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":[0.001521487,0.000606567,0.000754931,0.002921645,0.0003299196,0.001193681,0.0005541621,0.001020431,0.003152527],"category_scores_gemma":[0.01388835,0.0002931181,0.0008165552,0.002102295,0.0003057404,0.001734631,0.0006045895,0.0007404244,0.0008140086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006685402,"about_ca_system_score_gemma":0.0004918501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00658278,"about_ca_topic_score_gemma":0.008469111,"domain_scores_codex":[0.9992135,0.0003034261,0.00003481819,0.0001455747,0.0001795345,0.0001232878],"domain_scores_gemma":[0.9915754,0.006119571,0.001108637,0.0003679933,0.0005514268,0.000277001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001140857,0.001447081,0.7751763,0.0001657917,0.0004274776,0.0003582875,0.0007745171,0.05145684,0.009665195,0.007066307,0.001828482,0.1504928],"study_design_scores_gemma":[0.0000717136,0.0005118233,0.3139535,0.00001843942,0.0001522061,0.0001467815,0.0003404717,0.6674972,0.002413697,0.01394414,0.0008953081,0.00005491435],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818406,0.000123518,0.0143913,0.0002020688,0.000009159665,0.00007225732,0.0005313738,0.0000704811,0.002759339],"genre_scores_gemma":[0.9919166,0.00008618765,0.00701843,0.00003594834,0.00002305462,0.00003279542,0.0005003443,0.000009385647,0.0003772519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00658278,"threshold_uncertainty_score":0.01308888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01994643852202078,"score_gpt":0.2445148498886373,"score_spread":0.2245684113666165,"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."}}