{"id":"W4408723501","doi":"10.1021/acs.analchem.4c06519","title":"Rational Design of a New Class of Versatile Enzyme-Based Biosensors","year":2025,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Electrochemical sensors and biosensors","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Faculté de pharmacie, Université de Montréal; Association canadienne du médicament générique; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; China Scholarship Council","keywords":"Chemistry; Biosensor; Rational design; Enzyme; Combinatorial chemistry; Class (philosophy); Nanotechnology; Biochemical engineering; Biochemistry; Artificial intelligence","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":[0.000765569,0.0007655362,0.001026915,0.0003935334,0.0001990753,0.0007752026,0.0009571744,0.0009006779,0.0005813725],"category_scores_gemma":[0.0006600601,0.0005955481,0.0004365152,0.00038286,0.000468473,0.0008989396,0.0004275077,0.00111228,0.0007072661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006900103,"about_ca_system_score_gemma":0.0005473676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003386326,"about_ca_topic_score_gemma":0.0006150925,"domain_scores_codex":[0.9995531,0.00006160475,0.00005146337,0.0001251257,0.0001569822,0.00005165731],"domain_scores_gemma":[0.999828,0.00004594295,0.00003525045,0.00001712185,0.00003396815,0.00003968144],"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":[0.00006290827,0.0001010322,0.0001986832,0.0002457595,0.00003035377,0.0001517842,0.0000391342,0.003949427,0.9761422,0.005111588,0.0001933078,0.01377373],"study_design_scores_gemma":[0.00006951814,0.000562128,0.0002951281,0.00001907877,0.00003651277,0.0003445482,0.00001789344,0.02166505,0.9553754,0.000724077,0.02085985,0.00003075057],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3527278,0.01244384,0.6245154,0.001158371,0.0003879938,0.001078156,0.000493694,0.001231167,0.005963516],"genre_scores_gemma":[0.565603,0.009054834,0.4177766,0.0005239382,0.0000809648,0.0009640217,0.0007811638,0.0001170144,0.005098457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001026915,"threshold_uncertainty_score":0.005006433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01091643769233564,"score_gpt":0.2225384799470883,"score_spread":0.2116220422547526,"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."}}