{"id":"W2266934901","doi":"10.1039/c6an00044d","title":"Au nanoparticle decorated graphene nanosheets for electrochemical immunosensing of p53 antibodies for cancer prognosis","year":2016,"lang":"en","type":"article","venue":"The Analyst","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Graphene; Biosensor; Cyclic voltammetry; Raman spectroscopy; Nanoparticle; X-ray photoelectron spectroscopy; Electrode; Chemistry; Materials science; Colloidal gold; Oxide; Nanotechnology; Electrochemistry; Chemical engineering; Organic 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":[],"consensus_categories":[],"category_scores_codex":[0.0002232949,0.0001375618,0.0002243334,0.00004137829,0.0001398906,0.000009769746,0.0001501438,0.00008411375,7.449704e-7],"category_scores_gemma":[0.0001160124,0.00007461267,0.0002342886,0.0001742953,0.0001865068,0.000004462229,0.00004051594,0.00002310298,1.797642e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002042753,"about_ca_system_score_gemma":0.00005099316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003735104,"about_ca_topic_score_gemma":0.0001829669,"domain_scores_codex":[0.9990891,0.00003363878,0.0002557,0.000260447,0.00007846854,0.000282712],"domain_scores_gemma":[0.9991357,0.00005774359,0.000171186,0.0002798765,0.000323464,0.00003208479],"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":[0.0002401828,0.00003894539,0.001979307,0.0000137778,0.0002663886,9.794779e-8,0.00001463415,0.000001384368,0.9920021,0.00004883909,0.0002849057,0.005109412],"study_design_scores_gemma":[0.0003425649,0.0002064249,0.0002514676,0.00003780504,0.0002209689,0.000002020282,0.00003108993,0.0001284523,0.9966075,0.0003584607,0.001677513,0.0001356634],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792953,0.000463158,0.01914637,0.0007124788,0.00002725292,0.0002730138,0.00004642445,0.00002184458,0.00001412747],"genre_scores_gemma":[0.9956253,0.0002795546,0.003676808,0.00008057393,0.0001087616,0.00004866385,0.0000373394,0.00001777821,0.000125214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01632998,"threshold_uncertainty_score":0.3042616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01371449730542052,"score_gpt":0.2976725279135483,"score_spread":0.2839580306081277,"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."}}