{"id":"W4399279370","doi":"10.3386/w32515","title":"Understanding Expert Choices Using Decision Time","year":2024,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Computer science; Data science; Management science; Artificial intelligence; Engineering","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":[0.004353729,0.0002716139,0.0004542659,0.002230113,0.0002074819,0.000736245,0.000815539,0.0003868626,0.003822664],"category_scores_gemma":[0.001174478,0.0002532111,0.0001821429,0.0006312205,0.0002460097,0.001196032,0.0007456983,0.0006196559,0.002635402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00230599,"about_ca_system_score_gemma":0.00157719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003453693,"about_ca_topic_score_gemma":0.0001510439,"domain_scores_codex":[0.995952,0.00001775188,0.0007233711,0.0006786696,0.002206746,0.0004214901],"domain_scores_gemma":[0.9969949,0.0006251989,0.0003458523,0.0003382193,0.001674721,0.00002109352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000741648,0.00007255096,0.0002427301,0.001005793,0.0002133005,0.00001908189,0.00001228116,0.000772157,0.0007309896,0.3699736,0.6227348,0.004148591],"study_design_scores_gemma":[0.0001322879,0.000007772882,0.00003076688,0.001299767,0.00003516159,0.00001525528,0.00005032921,0.02107576,0.0001010629,0.5749113,0.4019744,0.0003661822],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001486663,0.002419533,0.0004513133,0.0006535677,0.002727136,0.000453112,0.0000771075,0.00006667479,0.9916649],"genre_scores_gemma":[0.9331636,0.003007898,0.001196304,0.0003097519,0.02926737,0.0001030375,0.002809346,0.000394686,0.02974803],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9619169,"threshold_uncertainty_score":0.999992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7772247054156955,"score_gpt":0.5597487248326142,"score_spread":0.2174759805830814,"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."}}