{"id":"W3034662952","doi":"10.1109/lsens.2020.3002446","title":"Aptamer-Enhanced Organic Electrolyte-Gated FET Biosensor for High-Specificity Detection of Cortisol","year":2020,"lang":"en","type":"article","venue":"IEEE Sensors Letters","topic":"Organic Electronics and Photovoltaics","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biosensor; Aptamer; Organic field-effect transistor; Biomolecule; Nanotechnology; Materials science; Electrolyte; Dielectric; Transistor; Field-effect transistor; Chemistry; Optoelectronics; Electrode; Electrical engineering; Biology","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":[0.00005853515,0.0002596059,0.0003578909,0.00007588558,0.00006443737,0.00002188937,0.0001593354,0.0001294951,0.00003505207],"category_scores_gemma":[0.00003585168,0.0002886318,0.0001138975,0.0004410553,0.00004003334,0.00006560638,0.000008636829,0.0002957915,0.00003306104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001362761,"about_ca_system_score_gemma":0.0000187094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001836513,"about_ca_topic_score_gemma":0.00002965869,"domain_scores_codex":[0.9986268,0.00002793278,0.0003894486,0.0003030641,0.000174592,0.0004782029],"domain_scores_gemma":[0.9994113,0.00008114482,0.0001030149,0.0002213124,0.0000663294,0.0001168673],"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":[0.00008811561,0.00001331034,0.000004323709,0.00007802605,0.0001005519,0.000002671796,0.0001719298,0.003716097,0.9940789,0.00001939785,0.001402335,0.000324299],"study_design_scores_gemma":[0.0006409149,0.0002911387,0.00003560946,0.000008785744,0.00004648528,0.000002727457,0.00002048406,0.01375309,0.9836883,0.00002787055,0.001186982,0.0002976364],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9670064,0.00005790258,0.0308134,0.0008136775,0.000436507,0.0004572792,0.00005795696,0.0003308957,0.00002591042],"genre_scores_gemma":[0.9983646,0.0000884539,0.000285207,0.0008098642,0.0002938233,0.000009849119,0.00001784471,0.0001080226,0.00002232694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03135813,"threshold_uncertainty_score":0.9999566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008038101777000189,"score_gpt":0.1833691694374873,"score_spread":0.1753310676604871,"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."}}