{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000453434,0.0007158397,0.0003205906,0.0003335718,0.0001890064,0.0005424956,0.0005208704,0.001100166,0.0005748355],"category_scores_gemma":[0.0005706602,0.0003024937,0.0002451707,0.0001669564,0.0004289371,0.0006491566,0.0003931663,0.000526724,0.0006291997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004413854,"about_ca_system_score_gemma":0.0003724582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001825613,"about_ca_topic_score_gemma":0.0004435788,"domain_scores_codex":[0.9997332,0.00005208291,0.00002208743,0.00008129182,0.00008291429,0.00002846702],"domain_scores_gemma":[0.9996778,0.00008824581,0.0001020494,0.0000305244,0.00007016433,0.00003126777],"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":[0.00001566937,0.0000112893,0.0001092213,0.00008264271,0.000003414463,0.00003079374,0.00001246484,0.0001199742,0.9949734,0.0003885779,0.00006392848,0.004188572],"study_design_scores_gemma":[0.000006893662,0.00008880373,0.0003179668,0.000008390381,0.0000114284,0.0001719308,0.00001192345,0.002476256,0.9927921,0.0001768233,0.003927162,0.00001024218],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4356439,0.00944213,0.5476258,0.001004347,0.0003905481,0.0005848096,0.000468816,0.001212592,0.003627018],"genre_scores_gemma":[0.5789883,0.00405282,0.4115382,0.0004820567,0.00008545457,0.0005515368,0.0003248164,0.00008697811,0.003889822],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001100166,"threshold_uncertainty_score":0.003202498,"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."}}