{"id":"W2382967911","doi":"","title":"Removal of the Baseline Drift in MagnetocardiogramUsing the Morphological Filter","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Baseline (sea); Computer science; Closing (real estate); Filter (signal processing); Feature (linguistics); Chose; Algorithm; Artificial intelligence; Real-time computing; Pattern recognition (psychology); Computer vision; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001912659,0.0001231524,0.0001399183,0.00006540086,0.0002970785,0.00002717484,0.001460908,0.00005000118,0.000004554877],"category_scores_gemma":[0.000001721413,0.00007722342,0.0001304691,0.001061825,0.0001936096,0.0001026794,0.0004827447,0.0001988452,0.00001301297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002951991,"about_ca_system_score_gemma":0.00005083915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001653463,"about_ca_topic_score_gemma":0.000002862322,"domain_scores_codex":[0.9988641,0.00007570557,0.0003445244,0.0003437539,0.0001835004,0.0001884848],"domain_scores_gemma":[0.9987985,0.0001713351,0.000124871,0.0007740548,0.0000987355,0.00003248596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001171225,0.0008478729,0.001453099,0.00002845707,0.00004299612,0.00009210422,0.00117435,0.03425461,0.02749325,0.381063,0.01224182,0.5412967],"study_design_scores_gemma":[0.0004055397,0.00003212568,0.03092142,0.00002676073,0.0000100536,0.00328692,0.00001252292,0.07658368,0.004633914,0.04701288,0.8367358,0.0003384041],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00724563,0.0001130082,0.9874185,0.003685557,0.00001346642,0.0007807748,0.000006351388,0.000104116,0.0006326277],"genre_scores_gemma":[0.2991806,0.00002254615,0.6989476,0.001244477,0.00007397776,0.0004275885,0.000005757596,0.000007754655,0.00008969849],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8244939,"threshold_uncertainty_score":0.314908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01951995192702115,"score_gpt":0.2496679590087526,"score_spread":0.2301480070817314,"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."}}