{"id":"W2033264218","doi":"10.1016/s1388-2457(01)00457-6","title":"Separation of spikes from background by independent component analysis with dipole modeling and comparison to intracranial recording","year":2001,"lang":"en","type":"article","venue":"Clinical Neurophysiology","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":73,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Independent component analysis; Electroencephalography; Dipole; Scalp; Epilepsy; Epileptic seizure; Pattern recognition (psychology); Spike (software development); Physics; Neuroscience; Artificial intelligence; Computer science; Medicine; Psychology; Anatomy","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":[0.0001478788,0.0001657631,0.0006577251,0.0001019572,0.0001403117,0.00002366269,0.0001597005,0.00007966788,0.00002876473],"category_scores_gemma":[0.001327395,0.0001401433,0.0001000904,0.0004292724,0.0002187195,0.0001007566,0.000178113,0.0002645175,0.00002311411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001717065,"about_ca_system_score_gemma":0.00001434362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002720729,"about_ca_topic_score_gemma":0.00009898388,"domain_scores_codex":[0.9977722,0.000445218,0.0005864709,0.000787819,0.0002020093,0.0002063333],"domain_scores_gemma":[0.9942136,0.005174608,0.0001853693,0.0002565326,0.0000631311,0.0001067839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002713362,0.0007036282,0.07065594,0.000008947398,0.0002028994,0.00002889856,0.0001027483,0.08992615,0.8323159,0.0001768011,0.0004921927,0.002672547],"study_design_scores_gemma":[0.001658611,0.003541468,0.2471939,0.00002188434,0.000427441,0.00001047544,0.000162463,0.7397538,0.005071727,0.0008381077,0.0008531074,0.0004669532],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9734392,0.00001857977,0.02470736,0.001274149,0.0002868613,0.0001642437,0.00002685531,0.00003254759,0.00005022613],"genre_scores_gemma":[0.9975993,0.00007449308,0.0003775274,0.001751844,0.0001414717,0.000009695247,0.00001082938,0.00001314319,0.00002168424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8272442,"threshold_uncertainty_score":0.571488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09555435654681241,"score_gpt":0.3709046644962319,"score_spread":0.2753503079494195,"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."}}