{"id":"W3195176773","doi":"10.3390/e23091105","title":"Memory and Markov Blankets","year":2021,"lang":"en","type":"article","venue":"Entropy","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Office of Naval Research; Engineering and Physical Sciences Research Council; Fonds National de la Recherche Luxembourg; Rosetrees Trust; Social Sciences and Humanities Research Council of Canada; Wellcome Trust; Wellcome","keywords":"Markov blanket; Blanket; Markov chain; Independence (probability theory); Computer science; Statistical physics; Set (abstract data type); Conditional independence; Argument (complex analysis); State (computer science); Simple (philosophy); Markov model; Mathematics; Markov property; Artificial intelligence; Algorithm; Epistemology; Statistics; Physics; Machine learning","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":[0.001288744,0.00028274,0.0005044309,0.0006277571,0.0007444765,0.001100612,0.0008664787,0.0008000554,0.004081069],"category_scores_gemma":[0.009237004,0.0002538428,0.0005918877,0.0003667642,0.003729604,0.004794432,0.001380611,0.001350328,0.000237769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001055115,"about_ca_system_score_gemma":0.0007199569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001837194,"about_ca_topic_score_gemma":0.001109484,"domain_scores_codex":[0.9996191,0.0001368003,0.00001866689,0.00007250741,0.00008127077,0.00007159969],"domain_scores_gemma":[0.9953648,0.003385097,0.0004450665,0.0004378898,0.0001686508,0.0001984959],"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":[0.00004874618,0.00001590333,0.0009793402,0.00005555612,0.00001943258,0.00008933472,0.0002178984,0.06209572,0.0009544881,0.9303076,0.0004436111,0.00477232],"study_design_scores_gemma":[0.00001157538,0.00003366996,0.0005930944,0.00001663451,0.000006530737,0.00005191667,0.00003618117,0.1273689,0.0004368723,0.8705509,0.0008773195,0.00001649591],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4887404,0.002941533,0.4689407,0.00327384,0.0001990325,0.00004643666,0.0002557032,0.0004582856,0.03514399],"genre_scores_gemma":[0.989211,0.00037819,0.008427201,0.0001188335,0.00007858222,0.00003389727,0.00004475439,0.00003600509,0.001671557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004081069,"threshold_uncertainty_score":0.01365256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01446114951910778,"score_gpt":0.2307510812527944,"score_spread":0.2162899317336866,"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."}}