{"id":"W3082167925","doi":"10.1109/embc44109.2020.9176489","title":"Pole-Zero REM Modeling with Application in EEG Artifact Removal","year":2020,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Overfitting; Computer science; Artifact (error); Noise (video); Algorithm; Minification; White noise; Probabilistic logic; Task (project management); Artificial intelligence; Speech recognition; Artificial neural network","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":[0.0006603678,0.001015509,0.0004990185,0.0005588876,0.0002913831,0.00042908,0.0007785414,0.0006195537,0.001231511],"category_scores_gemma":[0.0018354,0.0003511464,0.0007647131,0.0004511865,0.0003779606,0.0005799759,0.0005742526,0.0007311549,0.0006905299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002179073,"about_ca_system_score_gemma":0.0004339576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001730848,"about_ca_topic_score_gemma":0.002343735,"domain_scores_codex":[0.9996376,0.0001589859,0.00002090851,0.00005257661,0.0001066488,0.00002326785],"domain_scores_gemma":[0.9995958,0.0001558684,0.00005965301,0.00007225109,0.0001038906,0.00001250477],"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":[0.0002563907,0.00008896113,0.001072852,0.0003697284,0.0001192337,0.000496574,0.0002406821,0.6162364,0.07134263,0.03056904,0.002429063,0.2767785],"study_design_scores_gemma":[0.000005363124,0.00003983729,0.0001795828,0.00001356852,0.00001114756,0.0001372006,0.00001244442,0.9847347,0.009357105,0.00367176,0.00182205,0.00001521882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002588442,0.0001284869,0.9965269,0.00003086436,0.00001103212,0.00000984182,0.00001240254,0.0002154849,0.0004766257],"genre_scores_gemma":[0.2245208,0.0007068574,0.7700667,0.00009282558,0.00004869642,0.0001077129,0.0001712111,0.0002241503,0.00406115],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001730848,"threshold_uncertainty_score":0.004119873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02717552100056875,"score_gpt":0.2594303762139488,"score_spread":0.23225485521338,"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."}}