{"id":"W2790394912","doi":"10.1021/acs.bioconjchem.8b00067","title":"Gastrin-Releasing Peptide Receptor- and Prostate-Specific Membrane Antigen-Specific Ultrasmall Gold Nanoparticles for Characterization and Diagnosis of Prostate Carcinoma via Fluorescence Imaging","year":2018,"lang":"en","type":"article","venue":"Bioconjugate Chemistry","topic":"Gold and Silver Nanoparticles Synthesis and Applications","field":"Materials Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Bundesministerium für Wirtschaft und Energie; Bundesministerium für Bildung und Forschung","keywords":"Chemistry; Colloidal gold; Glutamate carboxypeptidase II; Prostate cancer; Biodistribution; In vivo; Positron emission tomography; Fluorescence; Peptide; Molecular imaging; Homogeneous; In vitro; Cancer research; Biophysics; Nanoparticle; Nanotechnology; Cancer; Internal medicine; Biochemistry; Nuclear medicine; Medicine; Materials science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003254846,0.0003830127,0.000175901,0.0003335353,0.0001221566,0.0001800558,0.0002408899,0.0004239266,0.0004817724],"category_scores_gemma":[0.0002343509,0.0001974318,0.0001487986,0.0001305379,0.0002255296,0.0002115103,0.0001930152,0.0002480047,0.000257509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003272097,"about_ca_system_score_gemma":0.0002276325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005602895,"about_ca_topic_score_gemma":0.0013417,"domain_scores_codex":[0.9998367,0.0000398923,0.00001189749,0.00003675367,0.00005372793,0.00002094828],"domain_scores_gemma":[0.9999228,0.00001810998,0.0000149009,0.00001168086,0.00001964748,0.00001292964],"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":[0.0000200025,0.000007887016,0.00007579703,0.00002610199,0.000001972484,0.00002429805,0.00001355983,0.0001533156,0.9974077,0.0001144984,0.00002972697,0.002125029],"study_design_scores_gemma":[0.000003825579,0.00005960053,0.0003830231,0.000001859367,0.000005388474,0.0001268117,0.000006057955,0.002787448,0.9957729,0.00003927059,0.0008099243,0.000003918579],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9158834,0.003390307,0.07745044,0.000284379,0.00005298466,0.0001144843,0.0001253361,0.0003201338,0.002378606],"genre_scores_gemma":[0.9437075,0.001160012,0.05116243,0.00009149944,0.00001287375,0.00006394389,0.0001624923,0.00003732329,0.003602024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005602895,"threshold_uncertainty_score":0.002374113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343662278747314,"score_gpt":0.2128175276540445,"score_spread":0.1993809048665713,"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."}}