{"id":"W4376110021","doi":"10.1016/j.bios.2023.115359","title":"A universal bacterial sensor created by integrating a light modulating aptamer complex with photoelectrochemical signal readout","year":2023,"lang":"en","type":"article","venue":"Biosensors and Bioelectronics","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Hamilton Health Sciences","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aptamer; Detection limit; Biosensor; Peptidoglycan; Nucleic acid; Chemistry; Colloidal gold; Nanotechnology; SIGNAL (programming language); DNA; Nanoparticle; Biophysics; Materials science; Chromatography; Biochemistry; Biology; Molecular biology; Enzyme; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001589143,0.0003648022,0.0003254299,0.0001109935,0.0002246998,0.00007623246,0.0001322728,0.0002730517,0.000008675344],"category_scores_gemma":[0.0000378603,0.0002805204,0.0001042098,0.0004782048,0.0001882952,0.000008757416,0.00009212895,0.0002248482,0.000003100105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004828871,"about_ca_system_score_gemma":0.00007388081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004690723,"about_ca_topic_score_gemma":0.00005720135,"domain_scores_codex":[0.9981154,0.00008176779,0.0002756153,0.000677077,0.0001966269,0.0006534687],"domain_scores_gemma":[0.9993023,0.00002378763,0.0001503475,0.0002565777,0.0001306844,0.0001362551],"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":[0.000357508,0.00003981536,0.0002328929,0.000009894289,0.0001214201,0.00001054507,0.0000305587,0.00000186064,0.994294,0.00003098237,0.002937934,0.001932615],"study_design_scores_gemma":[0.0006469616,0.001203065,0.00005156793,0.00003012201,0.00006960691,0.00007229705,0.0002440452,0.003155622,0.9745867,0.00001870637,0.01945016,0.000471116],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981502,0.0001003908,0.0006504487,0.0003564806,0.0000160666,0.000205458,0.00006786361,0.0002125356,0.0002405625],"genre_scores_gemma":[0.993799,0.000317725,0.00392545,0.0001339888,0.0001701412,0.000006728314,0.001029675,0.00005047592,0.000566854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01970724,"threshold_uncertainty_score":0.9999647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007920441582682491,"score_gpt":0.2350405726703413,"score_spread":0.2271201310876588,"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."}}