{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004728202,0.0001971408,0.0001930327,0.0002632406,0.0002337327,0.0003153995,0.0001641456,0.00003461436,0.006100639],"category_scores_gemma":[0.0001458067,0.0001829346,0.00002419221,0.0004564832,0.00002635964,0.0005493288,0.0004278416,0.0001325343,0.00007984985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002023016,"about_ca_system_score_gemma":0.00001091268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003132151,"about_ca_topic_score_gemma":0.0008678904,"domain_scores_codex":[0.9988299,0.00003383326,0.0002435197,0.0003852377,0.0001995808,0.0003079361],"domain_scores_gemma":[0.9994069,0.0001502674,0.00007236649,0.0002537966,0.00009019062,0.00002645045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007852121,0.0000222023,0.9362441,0.0000389062,0.00002404162,0.0000354874,0.0001473769,0.000005565551,0.01980001,0.0001121198,0.008267526,0.03451744],"study_design_scores_gemma":[0.0004422074,0.000003928619,0.710567,0.00004108126,0.00004994117,0.000004906421,0.0004218203,0.0003030059,0.0001091274,0.00009494262,0.2877013,0.0002607777],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783813,0.00003922376,0.00004889442,0.002499345,0.0002530139,0.0002855021,0.00000916402,0.0001425864,0.01834099],"genre_scores_gemma":[0.9945476,0.000003583345,0.001299436,0.003010303,0.0004691821,0.000005747248,0.00003230224,0.00002595448,0.0006059085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2794338,"threshold_uncertainty_score":0.9948079,"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."}}