{"id":"W1986073166","doi":"10.1016/j.compind.2008.03.003","title":"Optimizing customer's selection for configurable product in B2C e-commerce application","year":2008,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Product (mathematics); Wizard; The Internet; Software; Selection (genetic algorithm); E-commerce; Software engineering; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003300206,0.0004243827,0.0003938088,0.00074964,0.0004296694,0.001018667,0.0003789257,0.0004346017,0.004596413],"category_scores_gemma":[0.00142998,0.000217396,0.0002204726,0.0008098288,0.00008090936,0.0004961551,0.0002078248,0.0002362547,0.0007701515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004172323,"about_ca_system_score_gemma":0.0004439479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005568068,"about_ca_topic_score_gemma":0.007384946,"domain_scores_codex":[0.9996372,0.0001004978,0.00002255334,0.00006806174,0.0001071626,0.00006456025],"domain_scores_gemma":[0.9992155,0.0003255247,0.00007545113,0.00005943155,0.0002492373,0.00007495562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006106929,0.001962206,0.1024489,0.0001978985,0.0001245815,0.001317344,0.0003260922,0.08544916,0.2010669,0.001209326,0.01115603,0.5886347],"study_design_scores_gemma":[0.0001179887,0.0009623029,0.09460805,0.00001109473,0.0001586682,0.0006126478,0.0003705346,0.8164362,0.0836124,0.0004142248,0.002640143,0.00005578814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806488,0.0001593185,0.009870439,0.0001105447,0.00001338931,0.00006106181,0.0001125186,0.0006729614,0.008350925],"genre_scores_gemma":[0.9902688,0.00004246358,0.007414224,0.00003125766,0.000006102005,0.00001102274,0.0001359563,0.00004467766,0.002045494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005568068,"threshold_uncertainty_score":0.01537651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02421663792490512,"score_gpt":0.2315221257878543,"score_spread":0.2073054878629492,"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."}}