{"id":"W2969970279","doi":"","title":"Product Set Granularity and Consumer Response to Recommendations","year":2019,"lang":"en","type":"article","venue":"Monash University Research Portal (Monash University)","topic":"Consumer Behavior in Brand Consumption and Identification","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Network for Studies on Pensions, Aging and Retirement","keywords":"Granularity; Attractiveness; Product (mathematics); Computer science; Set (abstract data type); Marketing; Business; Mathematics; Psychology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001111959,0.0001970847,0.0002198781,0.001880418,0.0008331524,0.0002525394,0.0005487551,0.00009927359,0.001611974],"category_scores_gemma":[0.000139647,0.000252589,0.00009362549,0.001985068,0.0002558894,0.001600549,0.0007498251,0.0004241484,0.001749744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001290634,"about_ca_system_score_gemma":0.0001229103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001317304,"about_ca_topic_score_gemma":0.0008146208,"domain_scores_codex":[0.9978966,0.0001953624,0.0001652622,0.0007317341,0.0005319031,0.0004791871],"domain_scores_gemma":[0.9983963,0.0001487016,0.00009830414,0.0005441335,0.0006956622,0.0001168439],"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":[0.005892903,0.0008961014,0.7082682,0.0003159581,0.0002443332,0.000936279,0.0007265806,0.00001637783,0.02581,0.05909954,0.1218506,0.07594314],"study_design_scores_gemma":[0.0009470548,0.00001438075,0.2505309,0.00003510556,0.00005095643,0.00000475679,0.002846808,0.00006181269,0.00005641905,0.0001066983,0.7450616,0.0002834841],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9788364,0.0000260018,0.00002991572,0.0044263,0.0002334685,0.0008488457,0.00005519638,0.0001528093,0.01539107],"genre_scores_gemma":[0.9546943,0.00007678258,0.00009606856,0.0001316497,0.0000497302,8.894441e-7,0.0001262502,0.00001864395,0.04480571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.623211,"threshold_uncertainty_score":0.9999926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06019082663323525,"score_gpt":0.2871736970168775,"score_spread":0.2269828703836423,"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."}}