{"id":"W2918149247","doi":"10.1109/isspit.2018.8642620","title":"Extraction of Fetal Electrocardiogram signals using Blind Source Extraction Based Parallel Linear Predictor Filter","year":2018,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"FastICA; Computer science; Blind signal separation; Pattern recognition (psychology); Independent component analysis; Artificial intelligence; Filter (signal processing); Extraction (chemistry); Sensitivity (control systems); Linear prediction; Algorithm; Engineering; Electronic engineering; Chemistry; Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006066763,0.0001766926,0.0002136884,0.0003051762,0.000131084,0.0001234149,0.0003796432,0.0001680571,0.0001387261],"category_scores_gemma":[0.00004443831,0.0001664697,0.000159938,0.0005312425,0.00008951578,0.001079238,0.00006082365,0.0002007855,0.00002890191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004888716,"about_ca_system_score_gemma":0.0001344268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007077641,"about_ca_topic_score_gemma":0.000008402482,"domain_scores_codex":[0.9982769,0.0001837512,0.0004172167,0.0003992089,0.0004519936,0.0002709313],"domain_scores_gemma":[0.998684,0.0001193648,0.0002755724,0.0005036895,0.0003297659,0.00008759088],"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":[0.0009700995,0.001072687,0.001350804,0.00005828564,0.0002096701,0.000008830358,0.001238757,0.0184076,0.9362093,0.004125041,0.005265298,0.03108358],"study_design_scores_gemma":[0.0008040662,0.0003877835,0.0003942288,0.00001719928,0.00001676641,0.00002313442,0.00001340918,0.7169649,0.2764138,0.0003798681,0.004407942,0.000176904],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0828298,0.00002032903,0.9142822,0.0001630692,0.0001487065,0.0003686915,0.000001163087,0.0005119988,0.001674009],"genre_scores_gemma":[0.6642565,0.000003506168,0.3350055,0.0002401388,0.0001949826,0.00001580712,0.00000454183,0.00001343067,0.0002656038],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6985573,"threshold_uncertainty_score":0.6788439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03726160221308574,"score_gpt":0.3237205217333775,"score_spread":0.2864589195202917,"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."}}