{"id":"W2953421850","doi":"10.1177/1059712319862774","title":"A tale of two densities: active inference is enactive inference","year":2019,"lang":"en","type":"article","venue":"Adaptive Behavior","topic":"Embodied and Extended Cognition","field":"Neuroscience","cited_by":225,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Australian Research Council; Canada First Research Excellence Fund; Social Sciences and Humanities Research Council of Canada; Wellcome Trust; Wellcome","keywords":"Inference; Free energy principle; Generative grammar; Interpretation (philosophy); Cognitive science; Computer science; Artificial intelligence; Bayesian inference; Conflation; Generative model; Epistemology; Machine learning; Psychology; Bayesian probability; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01265291,0.0009224486,0.001271259,0.00174785,0.002295573,0.007845701,0.003079475,0.005965676,0.009704731],"category_scores_gemma":[0.03226957,0.001014751,0.001701335,0.0009738197,0.02689861,0.02170871,0.005719995,0.008630231,0.001399652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002304092,"about_ca_system_score_gemma":0.001557935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002563315,"about_ca_topic_score_gemma":0.001520865,"domain_scores_codex":[0.9935651,0.003373718,0.0002711347,0.001299261,0.001204185,0.0002865789],"domain_scores_gemma":[0.9843656,0.01168809,0.0005156481,0.002231684,0.0008009282,0.0003981287],"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":[0.000009682635,0.00000449159,0.00007724616,0.00002543921,0.00001552016,0.00002863742,0.0004877398,0.0009628795,0.00009841762,0.9935627,0.000680309,0.004046941],"study_design_scores_gemma":[0.000004505298,0.000003157481,0.00003105636,0.00001759108,0.000004891588,0.00002639208,0.00005802778,0.003100141,0.0000834279,0.9935809,0.003081706,0.000008172765],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006499198,0.00210381,0.9057835,0.03482881,0.000729426,0.00004450191,0.0001386584,0.000269843,0.04960222],"genre_scores_gemma":[0.605001,0.002364287,0.3605265,0.009389169,0.001487241,0.0003492247,0.0002256655,0.0005858417,0.02007113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01265291,"threshold_uncertainty_score":0.06691575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05747332432810019,"score_gpt":0.329519605722772,"score_spread":0.2720462813946718,"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."}}