{"id":"W4413023049","doi":"10.1039/d5an00741k","title":"Electrochemical and plasmonic detection methods yield comparable analytical performance for DNA hybridization","year":2025,"lang":"en","type":"article","venue":"The Analyst","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de l'Économie, de la Science et de l'Innovation - Québec; Ministère de l'Économie, de l’Innovation et des Exportations du Québec","keywords":"Biosensor; Plasmon; DNA; Nanotechnology; DNA–DNA hybridization; Computational biology; Yield (engineering); Electrochemistry; Materials science; Biological system; Chemistry; Biology; Optoelectronics; Genetics; Electrode","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":[0.004536986,0.001511647,0.001669134,0.001487158,0.0004262981,0.002254955,0.002406298,0.002697985,0.002924763],"category_scores_gemma":[0.009557066,0.0009903229,0.0007708965,0.001230861,0.001114966,0.001977241,0.001387411,0.002308292,0.003883156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008097983,"about_ca_system_score_gemma":0.0005707293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002788422,"about_ca_topic_score_gemma":0.0005318238,"domain_scores_codex":[0.991608,0.001592481,0.0005917184,0.001824197,0.003921716,0.0004618226],"domain_scores_gemma":[0.9948068,0.002111688,0.0007164387,0.0005705841,0.001613983,0.0001805476],"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":[0.00007942709,0.00006208323,0.0004408109,0.0004433625,0.00004272443,0.00006251653,0.0001097592,0.0002155456,0.9701635,0.001383516,0.0004651274,0.02653171],"study_design_scores_gemma":[0.00001741048,0.0001778428,0.00130841,0.00004318003,0.00003351728,0.0004224759,0.00009029108,0.001422188,0.9859044,0.001106325,0.00943683,0.00003713254],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.184669,0.0225765,0.7572586,0.003071632,0.0009240591,0.0007021542,0.001747191,0.003951534,0.02509934],"genre_scores_gemma":[0.4515157,0.01002976,0.5118663,0.002274744,0.0004219112,0.001249159,0.001692664,0.0006306539,0.02031917],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004536986,"threshold_uncertainty_score":0.02399415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01350725347379777,"score_gpt":0.321864991577556,"score_spread":0.3083577381037583,"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."}}