{"id":"W1487627229","doi":"10.1109/iembs.2006.260679","title":"Detecting Determinism in EEG Signals using Principal Component Analysis and Surrogate Data Testing","year":2006,"lang":"en","type":"article","venue":"","topic":"Chaos control and synchronization","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Manitoba","funders":"","keywords":"Surrogate data; Principal component analysis; Noise (video); Computer science; Smoothness; Series (stratigraphy); Time series; State space; Benchmark (surveying); Pattern recognition (psychology); Artificial intelligence; Determinism; Algorithm; Mathematics; Statistics; Machine learning; Nonlinear system","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":[0.000250927,0.0001009497,0.0001974407,0.0001247078,0.00009942341,0.0000798777,0.0001003699,0.0000186699,0.00005087218],"category_scores_gemma":[0.00001067117,0.00009464553,0.00002792664,0.0003916265,0.00001655204,0.0001662977,0.0001436734,0.00006341487,0.000001290083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000168526,"about_ca_system_score_gemma":0.00002189257,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007155189,"about_ca_topic_score_gemma":0.0008225098,"domain_scores_codex":[0.999148,0.00004305537,0.0002705888,0.0002671987,0.00008696088,0.0001842576],"domain_scores_gemma":[0.9994934,0.0001319867,0.0001001252,0.0002131944,0.00003113209,0.00003011973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002721124,0.00003568226,0.9505247,0.000004614766,0.00005522266,0.000002624722,0.00003703787,0.01156025,0.01886207,0.0001418207,5.290414e-7,0.01877271],"study_design_scores_gemma":[0.0003767232,0.000005487078,0.1596854,0.00001036398,0.0001050997,6.279535e-7,0.00006393655,0.8384035,0.0009621971,0.0002632306,0.00001139559,0.0001120928],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9043853,0.00001967604,0.09452658,0.00000996974,0.00001462218,0.00008158254,0.00001368826,0.00001667574,0.0009319253],"genre_scores_gemma":[0.9949703,1.161281e-7,0.004813262,0.000006712687,0.00009415063,0.00000196981,0.00007817522,0.00000758306,0.00002777419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8268433,"threshold_uncertainty_score":0.9994562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04557144546854554,"score_gpt":0.2790282359042878,"score_spread":0.2334567904357423,"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."}}