{"id":"W7040039298","doi":"","title":"Pricing Better","year":2019,"lang":"en","type":"other","venue":"Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Value (mathematics); Pricing strategies; Dynamic pricing; Retail industry; Emerging technologies; Field (mathematics); Affect (linguistics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001449207,0.0003448958,0.0003493733,0.0008110169,0.001258265,0.006291819,0.0005466898,0.00162904,0.2211048],"category_scores_gemma":[0.009285894,0.0001593908,0.0005901828,0.001219976,0.001034516,0.00748482,0.001918055,0.002231532,0.03081486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001227031,"about_ca_system_score_gemma":0.000856413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002995532,"about_ca_topic_score_gemma":0.002939914,"domain_scores_codex":[0.9985363,0.0002437809,0.00007553962,0.0002559597,0.0006899796,0.0001983774],"domain_scores_gemma":[0.9970965,0.0004578953,0.0004556949,0.0008663547,0.0007472449,0.0003762324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002867134,0.0008594519,0.02974583,0.000405897,0.0001376742,0.0006053393,0.006787401,0.0007898916,0.003695699,0.35184,0.1744035,0.4304426],"study_design_scores_gemma":[0.00008312453,0.0003186395,0.04178463,0.000225845,0.00007633233,0.0007454479,0.004741133,0.001398534,0.001661985,0.08800324,0.8608721,0.00008894161],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1614159,0.001402385,0.008444925,0.0131235,0.001363219,0.0002221799,0.001688962,0.0006040363,0.8117349],"genre_scores_gemma":[0.6403455,0.001609448,0.004676167,0.00790623,0.0006402279,0.00009069016,0.001774409,0.0005849099,0.3423725],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2211048,"threshold_uncertainty_score":0.7396692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01446290390457425,"score_gpt":0.1940079578423545,"score_spread":0.1795450539377803,"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."}}