{"id":"W4410380172","doi":"10.3389/fnhum.2025.1566566","title":"Koopman-based linearization of preparatory EEG dynamics in Parkinson’s disease during galvanic vestibular stimulation","year":2025,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Vestibular and auditory disorders","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia; University of Lethbridge","funders":"","keywords":"Galvanic vestibular stimulation; Parkinson's disease; Vestibular system; Neuroscience; Stimulation; Linearization; Electroencephalography; Medicine; Physical medicine and rehabilitation; Disease; Psychology; Physics; Internal medicine; 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":[0.0002640178,0.0004556211,0.0002094457,0.0001393924,0.0001133995,0.0003218064,0.0002737569,0.0002529887,0.0007901291],"category_scores_gemma":[0.0007530166,0.0001903333,0.0004044684,0.0001121674,0.0003355702,0.000332879,0.0003007067,0.0004303747,0.0001675161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000241104,"about_ca_system_score_gemma":0.0004665751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004703595,"about_ca_topic_score_gemma":0.004189964,"domain_scores_codex":[0.9999326,0.0000233706,0.000003339147,0.00001648486,0.00001322466,0.00001086724],"domain_scores_gemma":[0.9998499,0.0000849559,0.00002478486,0.00001169899,0.0000197852,0.000008796601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001447249,0.00006083241,0.002453829,0.00009218373,0.00007732318,0.0001732477,0.0001938521,0.9279385,0.02783783,0.004177216,0.0004406461,0.03640983],"study_design_scores_gemma":[0.000002275424,0.0000277321,0.0008221348,0.000002738713,0.000004753216,0.00001848745,0.000008660325,0.9973533,0.0009496139,0.0007078868,0.00009793468,0.000004367732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3012401,0.0002258201,0.6958877,0.0001220928,0.00001654913,0.00004911258,0.0000967352,0.00032325,0.002038517],"genre_scores_gemma":[0.9797773,0.0001176058,0.0185806,0.00001552108,0.00000473146,0.00003974424,0.00008630651,0.00002639873,0.001351776],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004703595,"threshold_uncertainty_score":0.009352386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097528873256282,"score_gpt":0.2620700702633822,"score_spread":0.2510947815308194,"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."}}