{"id":"W2159742327","doi":"10.1109/iembs.2009.5334147","title":"Computer-assisted method for quantifying sleep eye movements that reflects medication effects","year":2009,"lang":"en","type":"article","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Eye movement; Venlafaxine; Rapid eye movement sleep; Linear discriminant analysis; Autoregressive model; Discriminant function analysis; Citalopram; Psychology; Antidepressant; Physical medicine and rehabilitation; Artificial intelligence; Computer science; Medicine; Psychiatry; Machine learning; Statistics; Mathematics","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":[0.00107763,0.0006363862,0.0005207682,0.002355845,0.0002509871,0.0004505507,0.0005229476,0.0005312463,0.003275029],"category_scores_gemma":[0.002117733,0.000227452,0.0002685689,0.001663923,0.000178744,0.0003775124,0.0003524485,0.000551779,0.001069822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000306942,"about_ca_system_score_gemma":0.0004572723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002019869,"about_ca_topic_score_gemma":0.004917295,"domain_scores_codex":[0.9990214,0.000227092,0.00005315131,0.0001895824,0.0004816765,0.0000270671],"domain_scores_gemma":[0.9987211,0.0005067096,0.0001584205,0.0001332734,0.0004474804,0.00003292672],"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":[0.0005620701,0.0002638666,0.01716862,0.0005856854,0.000181351,0.0001201741,0.0001942897,0.004524885,0.3034001,0.00171714,0.005256467,0.6660253],"study_design_scores_gemma":[0.0002775008,0.001729691,0.2346842,0.0001767228,0.0003847041,0.002833405,0.0002422058,0.4248943,0.3035783,0.002313396,0.02849574,0.0003898297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07754329,0.0008379085,0.909772,0.00008443401,0.0001520011,0.0007069095,0.00182244,0.004899875,0.004181158],"genre_scores_gemma":[0.2538373,0.0005960395,0.7379177,0.0001173014,0.00006305438,0.001273831,0.0009773811,0.000167581,0.005049807],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003275029,"threshold_uncertainty_score":0.01095611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09205540827848831,"score_gpt":0.3920116638233859,"score_spread":0.2999562555448976,"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."}}