{"id":"W4226441215","doi":"10.1039/d2sd00042c","title":"Comparing two cortisol aptamers for label-free fluorescent and colorimetric biosensors","year":2022,"lang":"en","type":"article","venue":"Sensors & Diagnostics","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; University of Waterloo","keywords":"Aptamer; Biosensor; Fluorescence; Colorimetry; DNA; Chemistry; Nanotechnology; Biophysics; Computational biology; Biology; Biochemistry; Molecular biology; Chromatography; Materials science; Optics; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002077078,0.0002345408,0.0002879273,0.0001560982,0.0003855369,0.00003146101,0.0002306241,0.00007827928,0.000002445883],"category_scores_gemma":[0.0008580761,0.0002426338,0.0001054981,0.0003165373,0.000166636,0.000003124418,0.0004259987,0.0001628038,0.000001052552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004909721,"about_ca_system_score_gemma":0.00003507708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003267781,"about_ca_topic_score_gemma":0.0000390992,"domain_scores_codex":[0.9985095,0.0000901969,0.0002947432,0.0005046189,0.0002165363,0.0003844073],"domain_scores_gemma":[0.998947,0.0001808399,0.0001626312,0.0004669056,0.0001225441,0.0001201179],"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":[0.0007515507,0.000762047,0.04287855,0.00008602867,0.000509615,0.00006985835,0.0001357128,0.0007710577,0.8895128,0.0009731256,0.04914247,0.01440719],"study_design_scores_gemma":[0.003833249,0.002667567,0.003202669,0.00002895078,0.000432438,0.0001128344,0.0007673572,0.006718471,0.9080886,0.0005070618,0.07250641,0.001134457],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970917,0.0007888351,0.0007282259,0.0002804554,0.0001938433,0.0004866736,0.0002277593,0.00007731346,0.0001251649],"genre_scores_gemma":[0.9848774,0.001178812,0.01288057,0.0003746208,0.0001696514,0.00004631755,0.000238814,0.00004279434,0.0001909957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03967588,"threshold_uncertainty_score":0.9894321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01857871778834128,"score_gpt":0.2805280314500327,"score_spread":0.2619493136616914,"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."}}