{"id":"W4232924332","doi":"10.36227/techrxiv.14378888","title":"Detection of Epileptic Seizures from EEG Signals by Combining Dimensionality Reduction Algorithms with Machine Learning Models","year":2021,"lang":"en","type":"preprint","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université de Montréal","keywords":"Artificial intelligence; Dimensionality reduction; Pattern recognition (psychology); Computer science; Random forest; Curse of dimensionality; Discrete wavelet transform; Frequency domain; Entropy (arrow of time); Electroencephalography; Machine learning; Classifier (UML); Time domain; Wavelet; Wavelet transform","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006208435,0.0008232986,0.0008461536,0.001269539,0.0001907684,0.0008588171,0.0003643159,0.0004562848,0.0007646031],"category_scores_gemma":[0.001841217,0.0002216838,0.000852068,0.0008432468,0.000216115,0.0009160479,0.0003943256,0.0005197025,0.0005888371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002096679,"about_ca_system_score_gemma":0.0003780538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001384747,"about_ca_topic_score_gemma":0.001311113,"domain_scores_codex":[0.9995739,0.0001354103,0.00004277181,0.00008809764,0.0001317579,0.00002802971],"domain_scores_gemma":[0.999619,0.0001686501,0.0000597655,0.00005846717,0.00008554646,0.000008416674],"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":[0.00008875104,0.0001446748,0.002954738,0.0001998026,0.0001733655,0.0001220186,0.00008109253,0.1358735,0.02589244,0.003758178,0.002898702,0.8278127],"study_design_scores_gemma":[0.000006019939,0.00007443341,0.002211944,0.00001933852,0.000033205,0.000146838,0.00002896524,0.9851634,0.00747843,0.002832687,0.001985308,0.00001950068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02956683,0.001157647,0.9663688,0.0002507617,0.00007925537,0.00008504028,0.0001436804,0.001171478,0.0011765],"genre_scores_gemma":[0.3426387,0.001973842,0.6511762,0.0001513454,0.0001679789,0.0002646507,0.00103384,0.00009846062,0.002494939],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001384747,"threshold_uncertainty_score":0.003283381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04216863647962098,"score_gpt":0.2650548799978707,"score_spread":0.2228862435182497,"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."}}