{"id":"W3123136913","doi":"10.3386/w24284","title":"Human Judgment and AI Pricing","year":2018,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Economics; Computer science","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":[0.004408705,0.0004131221,0.0004686507,0.001291651,0.0006550792,0.004674116,0.0008408288,0.001877254,0.009221861],"category_scores_gemma":[0.03517085,0.00026873,0.0003669266,0.001233634,0.004317524,0.004432406,0.001187745,0.00188967,0.001143208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001963564,"about_ca_system_score_gemma":0.001250607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004723392,"about_ca_topic_score_gemma":0.002268418,"domain_scores_codex":[0.9972484,0.00134224,0.0001145596,0.000420168,0.0006905157,0.000184128],"domain_scores_gemma":[0.9898658,0.006434999,0.001000851,0.001017186,0.001192525,0.0004885438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001803588,0.0001557405,0.009232134,0.0002811723,0.000114813,0.0001866588,0.00137944,0.01636722,0.001062703,0.8360838,0.009686659,0.1252692],"study_design_scores_gemma":[0.00001417022,0.00002034149,0.003184208,0.00003516497,0.000009791201,0.00006710395,0.0002076556,0.01440059,0.0001542137,0.9767957,0.005092627,0.00001843837],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.239169,0.02145641,0.2640116,0.05520133,0.001309265,0.0001210687,0.000578325,0.0004533307,0.4176998],"genre_scores_gemma":[0.9778399,0.002173206,0.01302691,0.0009397512,0.0003340074,0.00002372451,0.0001218609,0.00004212476,0.005498445],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009221861,"threshold_uncertainty_score":0.03085017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6095459670727709,"score_gpt":0.6259604537499301,"score_spread":0.01641448667715928,"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."}}