{"id":"W2961677907","doi":"10.3390/bios9030088","title":"Diazonium-Modified Screen-Printed Electrodes for Immunosensing Growth Hormone in Blood Samples","year":2019,"lang":"en","type":"article","venue":"Biosensors","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Canada Research Chairs; University of Toronto; Canada Foundation for Innovation","keywords":"Dielectric spectroscopy; X-ray photoelectron spectroscopy; Surface plasmon resonance; Electrode; Chemistry; Biosensor; Electrochemistry; Glassy carbon; Materials science; Cyclic voltammetry; Analytical Chemistry (journal); Chromatography; Nanotechnology; Chemical engineering; Nanoparticle","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":[0.0005372408,0.0006931555,0.0004209928,0.0005310618,0.0001597365,0.0003019834,0.0009656684,0.0008766062,0.000643912],"category_scores_gemma":[0.001046402,0.0003764798,0.0002975599,0.0003550129,0.0002371989,0.0003142767,0.0003117126,0.0005717485,0.0005901353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002446514,"about_ca_system_score_gemma":0.0001970349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002807022,"about_ca_topic_score_gemma":0.0007673096,"domain_scores_codex":[0.9990867,0.0001648164,0.00005802819,0.0002067592,0.0004404134,0.00004319904],"domain_scores_gemma":[0.9995553,0.0002160365,0.00005147875,0.000036585,0.0001140052,0.00002652566],"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":[0.00003499326,0.00001085738,0.0001357824,0.0000802444,0.00001280354,0.00008735454,0.000007859338,0.0001184169,0.9957423,0.00005309115,0.00006545294,0.003650778],"study_design_scores_gemma":[0.000007065665,0.0001027337,0.0007944976,0.000005845221,0.00001896483,0.0003337417,0.000008654393,0.002718433,0.9946515,0.0000486971,0.001301133,0.00000871655],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5915548,0.01385862,0.3852969,0.0007008815,0.0007888121,0.0004341903,0.001170179,0.001954437,0.004241094],"genre_scores_gemma":[0.6941134,0.005886253,0.2936342,0.0004807063,0.0001238623,0.0003421934,0.0006910832,0.00007470605,0.004653669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009656684,"threshold_uncertainty_score":0.002841294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136872889391641,"score_gpt":0.2570887847204271,"score_spread":0.2457200558265107,"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."}}