{"id":"W3113280510","doi":"10.1098/rstb.2019.0692","title":"Out of the blue: understanding abrupt and wayward transitions in thought using probability and predictive processing","year":2020,"lang":"en","type":"article","venue":"Philosophical Transactions of the Royal Society B Biological Sciences","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Institute of Neurosciences, Mental Health and Addiction; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Surprise; Phenomenology (philosophy); Perception; Feeling; Psychology; Transition (genetics); Cognitive psychology; Probabilistic logic; Phenomenon; Epistemology; Cognitive science; Social psychology; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003122903,0.0001058514,0.0001741734,0.00001057346,0.000625489,0.00002684624,0.0002451768,0.00009572111,0.000006222505],"category_scores_gemma":[0.0001706468,0.00005232025,0.0001497207,0.0005762139,0.002816337,0.0001093236,0.00004569887,0.0002905359,4.90297e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003798368,"about_ca_system_score_gemma":0.00003811846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008579677,"about_ca_topic_score_gemma":0.000003718273,"domain_scores_codex":[0.9987827,0.0001970428,0.0002404377,0.0003719204,0.0002425819,0.0001653456],"domain_scores_gemma":[0.9995362,0.0002120845,0.00009853796,0.00007600107,0.00001882981,0.0000583967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000485499,0.001140475,0.03822345,0.0006298003,0.00005800416,0.000001516776,0.01410551,0.1225751,0.7563174,0.06220867,0.000007125556,0.004247454],"study_design_scores_gemma":[0.0004822695,0.0005520367,0.01370985,0.0001326645,0.00005766595,0.000005801497,0.001254453,0.7947334,0.01253249,0.1763114,0.000008344809,0.0002196119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.935191,0.00005122665,0.03353062,0.03060166,0.00008759352,0.000367317,0.00005430523,0.00001797093,0.00009824162],"genre_scores_gemma":[0.9990917,0.00002784309,0.0004548194,0.0003907443,0.00002528319,0.000005159157,1.271262e-7,0.000002655732,0.000001611127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7437849,"threshold_uncertainty_score":0.9998974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1931065556640127,"score_gpt":0.2960049135232563,"score_spread":0.1028983578592436,"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."}}