{"id":"W2021880533","doi":"10.1016/j.bios.2013.05.063","title":"Electrochemical impedance immunosensor based on gold nanoparticles–protein G for the detection of cancer marker epidermal growth factor receptor in human plasma and brain tissue","year":2013,"lang":"en","type":"article","venue":"Biosensors and Bioelectronics","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":193,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Colloidal gold; Epidermal growth factor receptor; Human Epidermal Growth Factor Receptor 2; Electrochemistry; Brain cancer; Electrical impedance; Biomedical engineering; Chemistry; Epidermal growth factor; Receptor; Human plasma; Dielectric spectroscopy; Materials science; Nanoparticle; Nanotechnology; Cancer; Biophysics; Chromatography; Medicine; Electrode; Biochemistry; Breast cancer; Internal medicine; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001679827,0.0002243654,0.0002281542,0.00006614134,0.0001067059,0.00002932273,0.00009936928,0.000206845,0.000002345806],"category_scores_gemma":[0.0001297316,0.0001596586,0.00007367955,0.0001464662,0.0001883446,0.000007706935,0.00003411453,0.0001473457,3.079616e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003814213,"about_ca_system_score_gemma":0.00003436759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001382204,"about_ca_topic_score_gemma":0.0002167759,"domain_scores_codex":[0.9987376,0.00007260429,0.0002886812,0.0004063874,0.0001063294,0.0003883603],"domain_scores_gemma":[0.9993919,0.00008899494,0.0001428143,0.0002134368,0.0001075665,0.00005529518],"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":[0.0002365534,0.00004829128,0.0002927583,0.00002711941,0.00003317976,1.680935e-7,0.000007452752,0.00000114504,0.9850581,0.00003787317,0.00007703718,0.01418033],"study_design_scores_gemma":[0.000569249,0.001030266,0.001173647,0.00003026048,0.00002093888,0.000002681859,0.0000216949,0.002251519,0.992954,0.00006445393,0.001660825,0.0002204955],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99669,0.001217305,0.0003460093,0.001079139,0.00001763486,0.0005975918,0.00002800934,0.00001812113,0.000006168917],"genre_scores_gemma":[0.9979475,0.0005671296,0.0009055794,0.0002111363,0.00007133349,0.00009356876,0.00001948746,0.00002440143,0.0001599208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01395984,"threshold_uncertainty_score":0.6510687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006677739898065599,"score_gpt":0.262682462540793,"score_spread":0.2560047226427274,"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."}}