{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002509949,0.0007674386,0.0009428855,0.001783188,0.0003419505,0.001073928,0.0006622166,0.0008528149,0.0006192535],"category_scores_gemma":[0.01546224,0.0002816439,0.0006520504,0.001002605,0.0009391307,0.001304788,0.0009053375,0.0008990793,0.0001745508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002472416,"about_ca_system_score_gemma":0.0007081736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003417479,"about_ca_topic_score_gemma":0.0003516672,"domain_scores_codex":[0.9979589,0.0007604841,0.0002031456,0.0003671927,0.0006183691,0.00009183233],"domain_scores_gemma":[0.992169,0.004770513,0.001191196,0.0007993995,0.000850555,0.0002193919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001117092,0.0003823537,0.04023687,0.0004285008,0.0004416993,0.0009176632,0.0004016994,0.1753701,0.08972067,0.04617149,0.001495906,0.643316],"study_design_scores_gemma":[0.00003534996,0.0003808941,0.01072774,0.00002234716,0.00004178389,0.0006316516,0.00005068968,0.9429464,0.02257617,0.02141342,0.001082761,0.00009074454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06208322,0.0001484471,0.9366124,0.0001186055,0.00003505008,0.00004998482,0.00008388679,0.0003531425,0.0005152989],"genre_scores_gemma":[0.7047505,0.0001501619,0.2942256,0.00004314772,0.00005009615,0.0001271284,0.0002488877,0.00004197139,0.0003625401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002509949,"threshold_uncertainty_score":0.01327407,"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."}}