{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01222923,0.0001175803,0.0002798354,0.0008193689,0.0003817905,0.0002467629,0.0009095238,0.0001969452,0.001616461],"category_scores_gemma":[0.001179293,0.00010486,0.00008996308,0.0001950784,0.0006667898,0.0001446054,0.001121971,0.0005750704,0.0005787789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002853733,"about_ca_system_score_gemma":0.0004605248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009985454,"about_ca_topic_score_gemma":0.00002809533,"domain_scores_codex":[0.9967227,0.0003096079,0.0007600929,0.0006866727,0.001317453,0.0002034881],"domain_scores_gemma":[0.9962342,0.001372743,0.000330233,0.0005395382,0.001419015,0.0001042965],"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":[0.00001129042,0.00003945545,0.0005521763,0.00001137321,0.00002843129,1.503354e-7,0.0001370898,0.0009073057,0.0002791784,0.9519895,0.04447924,0.001564801],"study_design_scores_gemma":[0.0001243409,0.000034668,0.001812065,0.00002217324,0.000002724193,0.000002038648,0.0001205969,0.001430295,0.0007865672,0.988971,0.006605089,0.00008846552],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4254424,0.0002654467,0.001359973,0.0135178,0.000640497,0.001370845,0.0001614722,0.0000414842,0.5572001],"genre_scores_gemma":[0.9924313,0.0000182344,0.0003920643,0.00007564148,0.0005237571,0.00009285525,0.00003331509,0.0000102596,0.006422564],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5669889,"threshold_uncertainty_score":0.9992962,"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."}}