{"id":"W1985238924","doi":"10.1109/stsiva.2012.6340587","title":"Detection of determinism in neuronal activity background from microelectrodes recording signals","year":2012,"lang":"en","type":"article","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Subthalamic nucleus; Microelectrode; Computer science; Premovement neuronal activity; Preprocessor; Multielectrode array; Neuroscience; Neurophysiology; SIGNAL (programming language); Process (computing); Pattern recognition (psychology); Artificial intelligence; Parkinson's disease; Medicine; Deep brain stimulation; Disease; Psychology; Pathology","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":[0.0007385166,0.0002891479,0.0004681038,0.0007585128,0.0001419845,0.0004454453,0.0003967401,0.0005763263,0.0004749661],"category_scores_gemma":[0.002863117,0.0001768615,0.0003071908,0.0004813264,0.0003826766,0.0004833307,0.0004777464,0.0004330643,0.0002033785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001542801,"about_ca_system_score_gemma":0.0001861615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001461127,"about_ca_topic_score_gemma":0.0002711117,"domain_scores_codex":[0.9994863,0.0001092668,0.00003116934,0.0001398274,0.0001983689,0.00003497412],"domain_scores_gemma":[0.9990268,0.0005552914,0.0001610902,0.0001186526,0.00009228531,0.00004590518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008939222,0.0001038744,0.01279497,0.0004777539,0.0000842228,0.0008342488,0.0004236946,0.03009465,0.5095673,0.01293407,0.0004636993,0.4313276],"study_design_scores_gemma":[0.0000265613,0.0008283524,0.05971529,0.00006750393,0.0000561388,0.00352108,0.0001725148,0.665354,0.244849,0.01852089,0.006803819,0.00008477087],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08007614,0.0002542548,0.9186416,0.00005125786,0.00002741457,0.00002218603,0.00008106742,0.0003018732,0.0005441883],"genre_scores_gemma":[0.7578676,0.0004054052,0.2403029,0.00002440459,0.00004319846,0.00004304519,0.0002563493,0.00005039019,0.001006717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0007585128,"threshold_uncertainty_score":0.003905714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05313547710479019,"score_gpt":0.2918863749068646,"score_spread":0.2387508978020745,"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."}}