{"id":"W4379351666","doi":"10.2139/ssrn.4467829","title":"Learning Customer Preferences from Bundle Sales Data","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Toronto","funders":"","keywords":"Bundle; Business; Marketing","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":[0.001790633,0.0001581204,0.0001690695,0.0002810208,0.0004437672,0.0004382461,0.0007603611,0.00005598491,0.0003527066],"category_scores_gemma":[0.0001618117,0.0001390385,0.00005777492,0.0005822806,0.00003178538,0.001269536,0.0004417238,0.001417722,0.001833543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007320942,"about_ca_system_score_gemma":0.0003033221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001169022,"about_ca_topic_score_gemma":0.003145069,"domain_scores_codex":[0.9976667,0.000031578,0.0002409389,0.0002954899,0.000307049,0.001458255],"domain_scores_gemma":[0.9993477,0.00009929379,0.0001834624,0.0002873486,0.00006681296,0.00001536416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008333419,0.00008126557,0.5239508,0.00003164031,0.0002021081,0.00001802212,0.0001400133,0.00008109792,0.0007288296,0.009587471,0.005253461,0.4598419],"study_design_scores_gemma":[0.002198953,0.00009894364,0.2294864,0.0002143505,0.0009078907,0.00007920056,0.01840686,0.00924475,0.00001992474,0.1981934,0.5396271,0.001522179],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905217,0.001035331,0.000235501,0.0005868648,0.0005116127,0.0000782651,0.000004328506,0.0002662691,0.006760145],"genre_scores_gemma":[0.9946011,0.001591348,0.00001536777,0.00008806946,0.001283914,0.000002920083,0.000246689,0.00003059623,0.002140035],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5343736,"threshold_uncertainty_score":0.9989436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04027164398034583,"score_gpt":0.2681548270591921,"score_spread":0.2278831830788463,"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."}}