{"id":"W2005512101","doi":"10.1287/mksc.1040.0109","title":"Overchoice and Assortment Type: When and Why Variety Backfires","year":2005,"lang":"en","type":"article","venue":"Marketing Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":450,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Regret; Variety (cybernetics); Set (abstract data type); Marketing; Product (mathematics); Product category; Business; Dimension (graph theory); Product type; Advertising; Computer science; Mathematics","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":[0.01134274,0.0004551289,0.000733963,0.001061927,0.001104738,0.003299083,0.0009434696,0.001675311,0.005910685],"category_scores_gemma":[0.0518712,0.0003782919,0.0009350958,0.001039746,0.00494061,0.003672068,0.002477946,0.001993196,0.0004979831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001305411,"about_ca_system_score_gemma":0.0005416638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00117269,"about_ca_topic_score_gemma":0.00113159,"domain_scores_codex":[0.9940058,0.002560468,0.0003179577,0.001051587,0.001690515,0.0003736626],"domain_scores_gemma":[0.9441583,0.03650429,0.008773547,0.006499336,0.001958401,0.002106056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003679319,0.001214266,0.6065761,0.0005187046,0.0008896296,0.0009314728,0.006448009,0.008254076,0.01563937,0.1174241,0.002575687,0.2358493],"study_design_scores_gemma":[0.0003294748,0.001189583,0.5731407,0.0002706469,0.0005152196,0.001301023,0.004670981,0.00996323,0.007971956,0.3874124,0.01302015,0.0002146511],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9645023,0.001671403,0.01358101,0.00215279,0.00007342669,0.00005645519,0.00006755951,0.00005966383,0.01783548],"genre_scores_gemma":[0.9965509,0.0003385039,0.001685785,0.0005076613,0.0000552176,0.00002294267,0.00002921533,0.00002385475,0.0007858298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01134274,"threshold_uncertainty_score":0.05998689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08857236628370567,"score_gpt":0.3841716594215719,"score_spread":0.2955992931378663,"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."}}