{"id":"W1627791142","doi":"","title":"Suppression of motion artifacts in optical action potential records by independent component analysis","year":2012,"lang":"en","type":"article","venue":"Computing in Cardiology","topic":"Cardiac electrophysiology and arrhythmias","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Independent component analysis; Artifact (error); Computer science; Component (thermodynamics); Signal processing; Motion (physics); Artificial intelligence; Motion analysis; SIGNAL (programming language); Pattern recognition (psychology); Blind signal separation; Computer vision; Telecommunications; Physics","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":[0.001068431,0.000534296,0.0003631548,0.001154855,0.0001954077,0.0004642429,0.0004289418,0.0004079994,0.001078634],"category_scores_gemma":[0.003684172,0.000138682,0.0003977218,0.0009714576,0.0003777297,0.0006509222,0.0002825745,0.0003815801,0.0005405103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009309567,"about_ca_system_score_gemma":0.0002579589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002891292,"about_ca_topic_score_gemma":0.0005396478,"domain_scores_codex":[0.999493,0.0001773889,0.00003851573,0.00007509638,0.000189005,0.00002703645],"domain_scores_gemma":[0.9989482,0.0005893242,0.0000822366,0.0001331345,0.0002278497,0.00001930696],"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":[0.0004997593,0.00008074672,0.001945976,0.0005066549,0.00008822472,0.0002190601,0.0001927985,0.003341633,0.5194018,0.001425809,0.0005230746,0.4717745],"study_design_scores_gemma":[0.0001541699,0.001946728,0.08757867,0.0001898568,0.0006142515,0.003208996,0.0002372337,0.2485052,0.6366854,0.005797434,0.01492756,0.0001545141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1380161,0.001566259,0.8564567,0.00009155583,0.00007030964,0.0002047014,0.0001607652,0.0009340966,0.002499433],"genre_scores_gemma":[0.4484981,0.001824315,0.5471637,0.00005574954,0.000156687,0.0002717919,0.0005135391,0.0002607953,0.001255193],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001154855,"threshold_uncertainty_score":0.005650461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01682279048203902,"score_gpt":0.2930994140979342,"score_spread":0.2762766236158952,"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."}}