{"id":"W2502992426","doi":"10.1021/acs.chemrev.6b00220","title":"Electrochemical Methods for the Analysis of Clinically Relevant Biomolecules","year":2016,"lang":"en","type":"review","venue":"Chemical Reviews","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":953,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Cancer Society Research Institute; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Genome Canada","keywords":"Biomolecule; Nanotechnology; Chemistry; Biomarker; Computational biology; Biochemical engineering; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001523522,0.00193774,0.001654141,0.003619322,0.0004999011,0.001602084,0.001840209,0.002423875,0.004923837],"category_scores_gemma":[0.001250862,0.0006825725,0.0008442883,0.003450854,0.0009723743,0.002230704,0.001517178,0.003952479,0.00701811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008835883,"about_ca_system_score_gemma":0.001076446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006921237,"about_ca_topic_score_gemma":0.001042069,"domain_scores_codex":[0.9987656,0.0001797306,0.0000854656,0.0002035139,0.0006907319,0.00007504186],"domain_scores_gemma":[0.9994783,0.00021981,0.00007147138,0.00003025645,0.0001706837,0.00002939842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006975844,0.0001589354,0.0002815542,0.01890451,0.0001551876,0.0005122226,0.0002230263,0.0007764791,0.04886803,0.02260055,0.0512323,0.8562174],"study_design_scores_gemma":[0.00001171869,0.00008539677,0.000262752,0.001213885,0.00004689462,0.001448114,0.00005400287,0.0002623314,0.009150232,0.004363663,0.9830592,0.0000418353],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002533571,0.9883485,0.005190763,0.0005476343,0.0008474419,0.00003390249,0.00004648917,0.00005497767,0.004676906],"genre_scores_gemma":[0.002892727,0.9852658,0.005348988,0.000607028,0.000482068,0.00007919792,0.0001008546,0.00001287259,0.005210452],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004923837,"threshold_uncertainty_score":0.01647192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06108517037992846,"score_gpt":0.4772815290915401,"score_spread":0.4161963587116117,"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."}}