{"id":"W3108742966","doi":"10.1162/neco_a_01341","title":"Deeply Felt Affect: The Emergence of Valence in Deep Active Inference","year":2020,"lang":"en","type":"article","venue":"Neural Computation","topic":"Embodied and Extended Cognition","field":"Neuroscience","cited_by":230,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"H2020 Marie Skłodowska-Curie Actions; Social Sciences and Humanities Research Council of Canada; Canada First Research Excellence Fund; Lundbeckfonden; Aarhus Universitets Forskningsfond; Rosetrees Trust; European Commission; Aarhus Universitet; Wellcome Trust; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; William K. Warren Foundation; McGill University","keywords":"Affect (linguistics); Inference; Valence (chemistry); Psychology; Computer science; Artificial intelligence; Cognitive psychology; Physics; Communication; Quantum mechanics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001148534,0.0003236429,0.0003477875,0.0001818474,0.0003364168,0.001506981,0.0007998301,0.0006742766,0.0013529],"category_scores_gemma":[0.007021125,0.0003621928,0.0003706294,0.0001449002,0.001198504,0.001389522,0.001379753,0.001632714,0.000119772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005140466,"about_ca_system_score_gemma":0.0003033532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007561784,"about_ca_topic_score_gemma":0.001082995,"domain_scores_codex":[0.9996303,0.0001539498,0.000013912,0.00007585178,0.00007299034,0.00005291708],"domain_scores_gemma":[0.9983668,0.001050808,0.0001975678,0.0001597075,0.0001181153,0.0001071443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005212296,0.000177904,0.01588694,0.0002059629,0.0002065739,0.0005081551,0.001505211,0.6207801,0.07570217,0.1780365,0.001517995,0.1049513],"study_design_scores_gemma":[0.00001535281,0.00004229091,0.001552026,0.00001142897,0.00001966376,0.00004432112,0.00004041481,0.9018268,0.004632107,0.09140231,0.0004005894,0.00001279543],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4401179,0.0002344064,0.5491436,0.001151037,0.00007276995,0.00003231079,0.00007948404,0.0002561996,0.008912255],"genre_scores_gemma":[0.9796013,0.00004547147,0.01952939,0.0001179472,0.00001317458,0.00001506344,0.00001997185,0.00002536286,0.0006321843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001506981,"threshold_uncertainty_score":0.006074131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07392864079283384,"score_gpt":0.3207362132718913,"score_spread":0.2468075724790575,"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."}}