{"id":"W3086260917","doi":"10.1016/j.electacta.2020.137094","title":"Simultaneous voltammetric detection of six biomolecules using a nanocomposite of titanium dioxide nanorods with multi-walled carbon nanotubes","year":2020,"lang":"en","type":"article","venue":"Electrochimica Acta","topic":"Electrochemical sensors and biosensors","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Canada Research Chairs","keywords":"Nanorod; Nanocomposite; Detection limit; Differential pulse voltammetry; Fourier transform infrared spectroscopy; Ascorbic acid; Nuclear chemistry; Titanium dioxide; Carbon nanotube; Materials science; Cyclic voltammetry; Electrochemical gas sensor; Chemistry; Analytical Chemistry (journal); Electrochemistry; Electrode; Chemical engineering; Nanotechnology; Chromatography; Physical chemistry","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":[0.00004359435,0.0003204279,0.0005120915,0.0001811742,0.00004241076,0.00001282274,0.0002166015,0.0001636234,0.000003980863],"category_scores_gemma":[0.0001192983,0.0002786377,0.0001280337,0.001183995,0.00006384427,0.00005231149,0.00003256762,0.0002560151,0.000001074133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009849572,"about_ca_system_score_gemma":0.00003463312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007468113,"about_ca_topic_score_gemma":0.00005663172,"domain_scores_codex":[0.9984753,0.00003277611,0.0004332133,0.0003212416,0.0002691459,0.0004683884],"domain_scores_gemma":[0.9992514,0.0001526547,0.000137155,0.0001995022,0.0001213889,0.0001378913],"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":[0.0002902712,0.00006492859,0.00008062799,0.0001465003,0.0001599054,0.000009075885,0.0001064905,0.00133086,0.9974974,0.000002100015,0.000003484711,0.0003083593],"study_design_scores_gemma":[0.0005977664,0.0005524647,0.00006112237,0.00004253139,0.00009182949,0.00003060506,0.00001637074,0.1242392,0.8740138,0.000002132852,0.00006738013,0.0002848032],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960417,0.0004095962,0.002926714,0.00004122428,0.00003475018,0.0002647295,0.000008052211,0.0001899768,0.00008324603],"genre_scores_gemma":[0.9954031,0.0000877669,0.004318858,0.0000302029,0.00006439805,0.000003846581,0.000006373706,0.00007443379,0.00001101913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1234836,"threshold_uncertainty_score":0.9999666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00809043250510403,"score_gpt":0.1965611662257807,"score_spread":0.1884707337206767,"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."}}