{"id":"W4375934522","doi":"10.1017/s0140525x22002643","title":"Hierarchical Bayesian narrative-making under variable uncertainty","year":2023,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Embodied and Extended Cognition","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Particle Physics","funders":"","keywords":"Narrative; Affect (linguistics); Bayesian probability; Probabilistic logic; Computer science; Mechanism (biology); Bayesian inference; Conviction; Artificial intelligence; Psychology; Cognitive psychology; Econometrics; Epistemology; Mathematics; Communication; Philosophy; Political science; Linguistics","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":[0.003546915,0.0002456731,0.0003139593,0.0002857911,0.0007050534,0.002331684,0.001230743,0.002166723,0.005510144],"category_scores_gemma":[0.02520691,0.0002391112,0.0003891564,0.000261204,0.003103485,0.004052094,0.001405788,0.003917599,0.0017356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002049327,"about_ca_system_score_gemma":0.001080814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002614508,"about_ca_topic_score_gemma":0.003738532,"domain_scores_codex":[0.9986312,0.0005994484,0.0000542136,0.0002236436,0.0003894466,0.0001020934],"domain_scores_gemma":[0.9935457,0.003860478,0.0005547617,0.0009190525,0.0007667785,0.0003531244],"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":[0.000078825,0.00001505499,0.0006735255,0.00003940339,0.00002104012,0.0001658683,0.0003075127,0.007599408,0.0004703107,0.9316689,0.0187795,0.04018057],"study_design_scores_gemma":[0.000008227432,0.000003658415,0.0002283453,0.00001156968,0.000002772991,0.00004041424,0.00002802626,0.01480481,0.0001833907,0.97853,0.00615155,0.000007317587],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.06339396,0.002009937,0.5236876,0.2320388,0.001805793,0.00008244364,0.0005340542,0.000710949,0.1757365],"genre_scores_gemma":[0.898829,0.001115241,0.07295705,0.01278053,0.0008758382,0.0001011685,0.0001662321,0.0001467937,0.0130281],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.005510144,"threshold_uncertainty_score":0.01875806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1104089916701988,"score_gpt":0.3569287963877409,"score_spread":0.246519804717542,"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."}}