{"id":"W2070450642","doi":"10.1021/ar500130m","title":"Ultrasensitive Electrochemical Biomolecular Detection Using Nanostructured Microelectrodes","year":2014,"lang":"en","type":"article","venue":"Accounts of Chemical Research","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":136,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Nanotechnology; Analyte; Microelectrode; Materials science; Potentiostat; Biomolecule; Biosensor; Multielectrode array; Multiplexing; Electrode; Computer science; Electrochemistry; Chemistry; Chromatography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005445297,0.0001702506,0.0002237062,0.000136696,0.00007788073,0.00002308377,0.0002465968,0.0002995334,0.000001809996],"category_scores_gemma":[0.001083167,0.0001545515,0.0001327893,0.0004087247,0.0004041243,0.0000062542,0.0001239775,0.0002893897,0.000001515323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005758944,"about_ca_system_score_gemma":0.00006641167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000408425,"about_ca_topic_score_gemma":0.000005255377,"domain_scores_codex":[0.998188,0.0001440007,0.0002500387,0.0004837325,0.0004450362,0.0004892026],"domain_scores_gemma":[0.9987337,0.00005849737,0.00008586549,0.0003973891,0.0006328362,0.00009170706],"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":[0.0001961948,0.00004225534,0.0000456812,0.00001357531,0.00004717807,8.934902e-7,0.000005338915,3.424933e-7,0.9962978,0.00002116785,0.0000626782,0.003266933],"study_design_scores_gemma":[0.0002124284,0.0001845494,0.00001989105,0.00001893017,0.00001876406,0.00003147537,0.00001429137,0.0003018518,0.9976579,0.0004759405,0.0008958591,0.0001681469],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920815,0.0001022742,0.007380587,0.00004869463,0.00001815072,0.0001199066,0.000006198011,0.00002094748,0.0002217924],"genre_scores_gemma":[0.9953978,0.00004070592,0.004184698,0.00006103416,0.0001968942,0.000003929043,0.00006161659,0.00002659373,0.00002670796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003316371,"threshold_uncertainty_score":0.6302427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01623880547799238,"score_gpt":0.3404278796069787,"score_spread":0.3241890741289863,"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."}}