{"id":"W4389542840","doi":"10.1109/embc40787.2023.10341128","title":"Implementing Effective Noise Reduction Techniques in Implantable NIRS Sensors","year":2023,"lang":"en","type":"article","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"SIGNAL (programming language); Noise (video); Computer science; Noise reduction; Bandwidth (computing); Electronic engineering; Amplifier; Interference (communication); Engineering; Artificial intelligence; Telecommunications","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":[0.0004238157,0.0005413784,0.000276875,0.0002816713,0.0001348503,0.0004466482,0.0009459047,0.0006076716,0.0006048895],"category_scores_gemma":[0.001027854,0.0002089468,0.0003871506,0.0001755469,0.0003361611,0.0005518718,0.0004005078,0.0003067697,0.0003370558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002780097,"about_ca_system_score_gemma":0.0001694686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002276586,"about_ca_topic_score_gemma":0.0002752733,"domain_scores_codex":[0.9994577,0.0001060212,0.00002918685,0.00009216922,0.0002853243,0.00002958092],"domain_scores_gemma":[0.9996643,0.0001275399,0.00006413617,0.00004456905,0.00008929385,0.00001017443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002005931,0.00008090556,0.000809215,0.000272732,0.00003375631,0.0002426543,0.0001219495,0.01574501,0.8631619,0.003880237,0.0006818681,0.1147692],"study_design_scores_gemma":[0.00003908306,0.0006380462,0.001586141,0.00004182217,0.00006677048,0.0006636613,0.00004227136,0.2461011,0.7354582,0.002338988,0.01296632,0.00005755635],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07314271,0.001318907,0.9218198,0.0001926549,0.0001486169,0.00006977717,0.00004065256,0.0009605122,0.0023064],"genre_scores_gemma":[0.6852896,0.0008206947,0.3110913,0.0003238686,0.00008633443,0.00008812846,0.00006056027,0.00007846459,0.002160989],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0009459047,"threshold_uncertainty_score":0.002241373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008295658245573963,"score_gpt":0.2470460952887474,"score_spread":0.2387504370431734,"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."}}