{"id":"W2227933157","doi":"10.1103/physreve.94.040301","title":"Pairwise network information and nonlinear correlations","year":2016,"lang":"en","type":"article","venue":"Physical review. E","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Education, Youth and Science; Grantová Agentura České Republiky","keywords":"Pairwise comparison; Bivariate analysis; Mutual information; Maximization; Nonlinear system; Joint probability distribution; Computer science; Entropy (arrow of time); Entropy maximization; Principle of maximum entropy; Mathematics; Mathematical optimization; Artificial intelligence; Machine learning; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.00007413348,0.00006406409,0.0001058624,0.00001117831,0.00007568123,0.00001722933,0.0000459974,0.00001091901,0.00001800732],"category_scores_gemma":[0.0005239442,0.00003725356,0.00004254779,0.0001480226,0.00003989063,0.0004037487,0.00003562797,0.00005246805,0.000314155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009691491,"about_ca_system_score_gemma":0.000008068791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001002754,"about_ca_topic_score_gemma":4.706196e-7,"domain_scores_codex":[0.9994943,0.00004242652,0.0001326596,0.0001077681,0.0001110983,0.0001118203],"domain_scores_gemma":[0.9994968,0.0002511984,0.00006855909,0.0001114246,0.00002004085,0.00005196145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002206795,0.00009976244,0.001166087,0.0002970255,0.000004367439,0.000001988255,0.00003913743,0.00004953199,0.05258314,0.1333097,0.01732962,0.7950976],"study_design_scores_gemma":[0.0007750806,0.0003048408,0.01051475,0.00181788,0.00007630601,0.00002378791,0.000002382724,0.08301104,0.003724505,0.05962434,0.8395858,0.0005392521],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9395182,0.001558868,0.0159833,0.02719182,0.001222592,0.001553813,0.00008355296,0.0003494171,0.01253851],"genre_scores_gemma":[0.9867387,0.007676817,0.0001058327,0.004947133,0.0002907797,0.00002233843,0.000005475414,0.00000663792,0.000206286],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8222562,"threshold_uncertainty_score":0.4037932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01938969186712518,"score_gpt":0.2858363340721329,"score_spread":0.2664466422050077,"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."}}