{"id":"W2965514669","doi":"10.1002/jbio.201900166","title":"Designable nanoplasmonic biomarkers for direct microscopy cytopathology diagnostics","year":2019,"lang":"en","type":"article","venue":"Journal of Biophotonics","topic":"Gold and Silver Nanoparticles Synthesis and Applications","field":"Materials Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; Polytechnique Montréal","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research","keywords":"Microscopy; Nanorod; Plasmon; Materials science; Cytopathology; Optical microscope; Nanotechnology; Surface plasmon resonance; Photothermal therapy; Optics; Nanoparticle; Pathology; Scanning electron microscope; Optoelectronics; Cytology; Medicine; Physics","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":[0.0006879999,0.0001089229,0.0002945265,0.00006863553,0.000090947,0.00006383532,0.0002697467,0.00007856419,0.0001478875],"category_scores_gemma":[0.0001164963,0.00008466844,0.0001516986,0.0001179993,0.00005600699,0.0001069484,0.00002891557,0.00006188947,0.0001088565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004943716,"about_ca_system_score_gemma":0.0001236327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004970742,"about_ca_topic_score_gemma":0.000001938024,"domain_scores_codex":[0.9989656,0.00004178432,0.0004265148,0.0001572527,0.000138398,0.0002704042],"domain_scores_gemma":[0.9987963,0.0003997537,0.0003490289,0.0002064151,0.0001596657,0.00008876693],"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":[0.00008452459,0.0001000984,0.001404892,0.0000197377,0.000012581,0.000004981046,0.00004620108,0.00004762432,0.9967369,0.0002383185,0.001036746,0.0002673723],"study_design_scores_gemma":[0.0005157986,0.0003174282,0.0005300417,0.00004134158,0.00004755512,0.00004961928,0.00006120035,0.0002005674,0.9807466,0.0002688777,0.01711172,0.0001092725],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973987,0.001011517,0.0002218322,0.0001989302,0.0006350197,0.0002498516,0.0000349775,0.00001217649,0.0002370212],"genre_scores_gemma":[0.9851446,0.0004910107,0.01403144,0.0001270347,0.00004391939,0.00001410121,0.000001118812,0.00001541684,0.0001313516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01607497,"threshold_uncertainty_score":0.3452679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009190726424774925,"score_gpt":0.2445190951048679,"score_spread":0.235328368680093,"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."}}