{"id":"W2052484123","doi":"10.1371/journal.pone.0053588","title":"Confounding Effects of Phase Delays on Causality Estimation","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto; Baycrest Hospital","funders":"James S. McDonnell Foundation","keywords":"Granger causality; Causality (physics); Synchronization (alternating current); Computer science; Ambiguity; Phase (matter); Phase synchronization; Autocorrelation; SIGNAL (programming language); Lag; Linear model; Artificial intelligence; Machine learning; Mathematics; Statistics; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0000574087,0.00006466622,0.0001096492,0.00004549677,0.00005662353,0.0000255719,0.00006108198,0.00002738021,0.00005250759],"category_scores_gemma":[0.0007614635,0.00005696215,0.00002070357,0.0001046047,0.00003385866,0.0001489816,0.00001609694,0.00007329872,0.0001376939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002369273,"about_ca_system_score_gemma":0.000006371965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000288695,"about_ca_topic_score_gemma":7.485763e-7,"domain_scores_codex":[0.9993324,0.0000538362,0.0001231645,0.0001589692,0.0002229652,0.0001086813],"domain_scores_gemma":[0.9993342,0.0003758894,0.00007935717,0.0001383535,0.0000318971,0.00004032102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001472744,0.0008569065,0.00007058869,0.0001055441,0.000005241399,0.000001862054,0.00002397198,0.00002663157,0.9939488,0.002826611,0.00003116965,0.00208793],"study_design_scores_gemma":[0.0004544915,0.0003959832,0.0007593238,0.00008370638,0.00001799379,6.225424e-7,0.000001395718,0.1164918,0.8802351,0.00149881,0.000002654024,0.00005811148],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976317,0.000002062838,0.0007061561,0.0001858517,0.0001045843,0.0003714147,0.000003555454,0.00004342095,0.0009512634],"genre_scores_gemma":[0.9991632,0.000004819072,0.000240609,0.0003309968,0.00002493903,0.00002737213,0.000003379261,0.000007377922,0.0001973574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1164652,"threshold_uncertainty_score":0.2322849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06045343731986253,"score_gpt":0.2837969915409975,"score_spread":0.2233435542211349,"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."}}