{"id":"W2734822630","doi":"10.1021/jacs.7b05412","title":"Calibration-Free Electrochemical Biosensors Supporting Accurate Molecular Measurements Directly in Undiluted Whole Blood","year":2017,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":226,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Army Research Office; Natural Sciences and Engineering Research Council of Canada; National Institute of Allergy and Infectious Diseases; Fonds de recherche du Québec – Nature et technologies; Eusko Jaurlaritza; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Biosensor; Calibration; Square wave; Chemistry; SIGNAL (programming language); Electrochemical gas sensor; Dynamic range; Accuracy and precision; Analytical Chemistry (journal); Biological system; Electrode; Electrochemistry; Optics; Computer science; Physics; Chromatography; Voltage","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004023613,0.0001768781,0.0003241815,0.00001939235,0.0001450302,0.00006480237,0.0008918069,0.0001073495,6.95975e-7],"category_scores_gemma":[0.0009420859,0.0001244195,0.000513767,0.0001532606,0.0004119701,0.00001446807,0.0002927749,0.0003179411,1.769022e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005433778,"about_ca_system_score_gemma":0.00009215713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002066632,"about_ca_topic_score_gemma":0.000006024672,"domain_scores_codex":[0.9985886,0.00007022393,0.0004620955,0.0002385557,0.0003359932,0.0003045416],"domain_scores_gemma":[0.9977988,0.0000173112,0.001280273,0.0006513164,0.0001639348,0.00008836191],"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":[0.00005414246,0.00008647241,0.00480206,0.000004323126,0.000171592,0.000004105546,0.00001531686,0.000003859041,0.9935889,0.000001170787,0.0009808125,0.0002872048],"study_design_scores_gemma":[0.0004799161,0.00008305275,0.001048501,0.00003249965,0.00009070456,0.00003879555,0.00004318528,0.00007058583,0.9975607,0.0001595368,0.0002319802,0.000160545],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971504,0.00007260122,0.0004641739,0.00213722,0.00003383389,0.0000669729,0.000005775717,0.000009005901,0.00006006062],"genre_scores_gemma":[0.9917256,0.00006841332,0.007384347,0.0005983029,0.0001619564,0.000001599314,0.000006739017,0.00001927147,0.00003379177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006920173,"threshold_uncertainty_score":0.507368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0133448545815734,"score_gpt":0.2931478795173844,"score_spread":0.279803024935811,"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."}}