{"id":"W4298009678","doi":"10.18280/ts.390429","title":"Medical Signal Processing via Digital Filter and Transmission Reception Using Cognitive Radio Technology","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Noise (video); SIGNAL (programming language); Filter (signal processing); Transmission (telecommunications); Electronic engineering; Analog signal; Speech recognition; Artificial intelligence; Telecommunications; Engineering; Computer vision","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002856373,0.0001521752,0.0002565071,0.000274495,0.0003487346,0.00003651519,0.00006651405,0.00008694961,0.002032716],"category_scores_gemma":[0.00001407216,0.0001364806,0.00007783133,0.0003705915,0.0001220189,0.0001261474,0.00005201629,0.00037196,0.000003123569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009438025,"about_ca_system_score_gemma":0.0001058822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007392659,"about_ca_topic_score_gemma":2.709808e-7,"domain_scores_codex":[0.9984478,0.00004742346,0.0002907811,0.0003185575,0.0006514695,0.000243939],"domain_scores_gemma":[0.9995905,0.00004046737,0.00007962932,0.00005510457,0.00006546148,0.0001688224],"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":[0.00033802,0.0003844511,0.01775063,0.00009141068,0.0001327931,0.0001620689,0.0006530052,0.00006493438,0.03776073,0.000004467995,0.00005735799,0.9426001],"study_design_scores_gemma":[0.0183455,0.005586128,0.009656422,0.002699463,0.002564361,0.003910543,0.01035809,0.9024088,0.0300549,0.000933463,0.01184723,0.001635101],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8792042,0.0005331913,0.1185879,0.001147021,0.00003535482,0.0002076554,0.00001231388,0.0001094579,0.0001628731],"genre_scores_gemma":[0.998512,0.00001604037,0.0008483374,0.0001295094,0.0002499915,0.00003073805,0.0000684329,0.00002116503,0.0001237958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9409651,"threshold_uncertainty_score":0.9988796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01999387095286752,"score_gpt":0.2744345313898639,"score_spread":0.2544406604369964,"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."}}