{"id":"W4392660940","doi":"10.1002/anie.202400413","title":"High‐Precision Viral Detection Using Electrochemical Kinetic Profiling of Aptamer‐Antigen Recognition in Clinical Samples and Machine Learning","year":2024,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University Medical Centre; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"False positive paradox; Aptamer; True positive rate; Coronavirus disease 2019 (COVID-19); Computer science; Profiling (computer programming); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); False positives and false negatives; Artificial intelligence; Gold standard (test); Computational biology; Machine learning; Virology; Pattern recognition (psychology); Biology; Medicine; Mathematics; Infectious disease (medical specialty); Molecular biology; Pathology; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001421009,0.0007684247,0.0007355238,0.0006590221,0.0001711785,0.0008618552,0.0006941017,0.001147919,0.0004858132],"category_scores_gemma":[0.001832,0.0004737561,0.0003790896,0.0006445116,0.000424216,0.0006255404,0.0004378611,0.0009714275,0.0004564362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003883255,"about_ca_system_score_gemma":0.0004243604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005370045,"about_ca_topic_score_gemma":0.001234034,"domain_scores_codex":[0.9986733,0.0003495158,0.00007602056,0.0003044287,0.00051213,0.00008453808],"domain_scores_gemma":[0.9993788,0.0003163691,0.0001092837,0.00007123611,0.0001038062,0.00002050317],"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":[0.0002319126,0.0001689496,0.00386374,0.0003013706,0.00008901925,0.000121635,0.000107677,0.00474125,0.9030443,0.001375841,0.0008999478,0.08505435],"study_design_scores_gemma":[0.00003918209,0.0004455277,0.004675955,0.00003663286,0.0000418593,0.0007258735,0.00006228447,0.08914679,0.8998017,0.001745371,0.00320541,0.00007347791],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2685462,0.007946618,0.715556,0.001145139,0.000344264,0.0002192407,0.0007233249,0.001562733,0.003956417],"genre_scores_gemma":[0.7178193,0.003182613,0.2750539,0.0005023871,0.0001322985,0.0002360359,0.0003599056,0.00006058194,0.002653077],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001421009,"threshold_uncertainty_score":0.007515073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02937088581218443,"score_gpt":0.3176296475776538,"score_spread":0.2882587617654693,"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."}}