{"id":"W3093312274","doi":"10.2139/ssrn.3628684","title":"Algorithmic Personalized Pricing","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Digitalization, Law, and Regulation","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Business; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00226431,0.0009173869,0.001572054,0.0009826509,0.001670254,0.004965806,0.002199556,0.003294163,0.03256371],"category_scores_gemma":[0.01779968,0.000653665,0.0008972696,0.002044662,0.00237748,0.006977041,0.002515115,0.004223486,0.003136973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002452375,"about_ca_system_score_gemma":0.002244146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001602399,"about_ca_topic_score_gemma":0.002756409,"domain_scores_codex":[0.9978279,0.00094132,0.00008328501,0.0004573218,0.0004512189,0.0002389607],"domain_scores_gemma":[0.9937091,0.00377153,0.0002571985,0.001530739,0.0004350008,0.0002964396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009038549,0.0001495792,0.0005701384,0.00007278389,0.00004858159,0.00004174441,0.0000928652,0.03318597,0.0003047062,0.9101903,0.01800452,0.03724831],"study_design_scores_gemma":[0.00002996192,0.00001886153,0.0001952267,0.00001662309,0.00001759107,0.00003818889,0.00002645646,0.1392998,0.0001422529,0.8541318,0.006069873,0.00001335461],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07078176,0.002414129,0.7031427,0.01507453,0.001258754,0.0002344499,0.0006820713,0.001279614,0.205132],"genre_scores_gemma":[0.8248501,0.001349185,0.08860853,0.001725071,0.001031464,0.000224662,0.0005924788,0.0003806967,0.08123779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03256371,"threshold_uncertainty_score":0.1089365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01402804595886032,"score_gpt":0.2677916340190308,"score_spread":0.2537635880601705,"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."}}