{"id":"W3008858078","doi":"10.1287/serv.2019.0250","title":"Product Return Episodes in Retailing","year":2019,"lang":"en","type":"article","venue":"Service Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Marketing; Product (mathematics); Profit (economics); New product development; Business; Economics; Computer science; Microeconomics","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":[],"consensus_categories":[],"category_scores_codex":[0.001338197,0.00009801477,0.000112281,0.0003231418,0.0001267361,0.00029122,0.000540175,0.00001882655,0.0003122087],"category_scores_gemma":[0.00009688169,0.00008943711,0.00001977476,0.002646246,0.00005549298,0.002016739,0.0002827969,0.0001324756,0.0006216152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002484796,"about_ca_system_score_gemma":0.00005403028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001640309,"about_ca_topic_score_gemma":0.001070082,"domain_scores_codex":[0.998758,0.000005445784,0.0001631191,0.0004107178,0.0003211665,0.0003416009],"domain_scores_gemma":[0.9993653,0.00002268967,0.0000745022,0.0003569268,0.0001705116,0.00001011467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001062299,0.00001780233,0.9399762,0.0001330131,6.61107e-7,0.00000342281,0.000136623,0.00003269846,0.04498661,0.001009797,0.00002106741,0.01367151],"study_design_scores_gemma":[0.0003638074,0.00000373212,0.9700722,0.00017495,0.00001418464,0.000003099819,0.0006379834,0.01734402,0.00178001,0.001561821,0.007668495,0.0003757635],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9540928,0.00005915725,0.000002526119,0.001429518,0.0004956736,0.0001944291,1.551574e-7,0.00006260752,0.04366315],"genre_scores_gemma":[0.9979386,0.000002145628,0.0001218568,0.001562333,0.0001239687,0.000003974219,0.000001324661,0.00000822375,0.0002375664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04384582,"threshold_uncertainty_score":0.7989813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0181167222334077,"score_gpt":0.24064062938602,"score_spread":0.2225239071526123,"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."}}