{"id":"W4392630864","doi":"10.1002/ange.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","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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":"Aptamer; Profiling (computer programming); Computer science; Computational biology; Virology; Chemistry; Combinatorial chemistry; Pattern recognition (psychology); Artificial intelligence; Molecular biology; Biology; Operating system","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":[0.001278851,0.0006458957,0.0005951146,0.0006307245,0.000135496,0.0007762571,0.0005017103,0.0009764308,0.0005238598],"category_scores_gemma":[0.001623095,0.0003326928,0.0002827672,0.0004954842,0.0003360113,0.0004541839,0.0003262323,0.000736544,0.0003663861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003214396,"about_ca_system_score_gemma":0.0003452376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005391617,"about_ca_topic_score_gemma":0.001011579,"domain_scores_codex":[0.9990169,0.0002911826,0.00005694332,0.0002323235,0.0003435514,0.00005904038],"domain_scores_gemma":[0.9993606,0.0003290784,0.0001049765,0.00007240727,0.0001115548,0.00002145761],"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":[0.0003427171,0.0002123041,0.00691938,0.0002698193,0.0001077935,0.0001259397,0.00009124358,0.00803361,0.9011129,0.001131867,0.00122492,0.08042772],"study_design_scores_gemma":[0.00004214446,0.000465402,0.007187108,0.00003249737,0.00003834981,0.0006267717,0.0000597145,0.1578712,0.829481,0.001520107,0.002612524,0.00006318445],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4079272,0.005545158,0.5784824,0.001209395,0.0003222643,0.0001841368,0.0009009693,0.001676796,0.003751679],"genre_scores_gemma":[0.8470038,0.001142389,0.1492396,0.0003325987,0.00008008157,0.0001304912,0.0002526143,0.00003856732,0.001779906],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001278851,"threshold_uncertainty_score":0.006763279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03380533475477794,"score_gpt":0.309630021356428,"score_spread":0.27582468660165,"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."}}