{"id":"W3180886807","doi":"10.3390/cancers13143509","title":"Multiplexed Plasmonic Nano-Labeling for Bioimaging of Cytological Stained Samples","year":2021,"lang":"en","type":"article","venue":"Cancers","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Multiplex; Immunolabeling; Multiplexing; Cytopathology; Microscopy; Microscope; Computer science; Biomedical engineering; Pathology; Materials science; Medicine; Cytology; Biology; Bioinformatics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004478526,0.00007400518,0.0001058168,0.00001210899,0.00005934932,0.000005473787,0.00007219481,0.00006362183,0.000003358244],"category_scores_gemma":[0.000116677,0.0000713134,0.00006609274,0.00006784903,0.00007154213,0.000001386244,0.00004693574,0.00003031549,2.093895e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005318452,"about_ca_system_score_gemma":0.0001951592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001212348,"about_ca_topic_score_gemma":0.0000214767,"domain_scores_codex":[0.9994557,0.000009919971,0.00012933,0.0002250517,0.00003695583,0.000143064],"domain_scores_gemma":[0.9995591,0.00002213283,0.00006267769,0.0001960742,0.0001302021,0.00002981566],"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":[0.00002940569,0.000006829585,0.0001138652,0.00001532659,0.00001533732,4.611428e-7,0.00000684858,0.0003278561,0.9959625,0.0005727846,0.0004203148,0.00252846],"study_design_scores_gemma":[0.0002867476,0.00005237544,0.00003499019,0.00001729472,0.000009460783,0.000003762384,0.00008682351,0.0004450328,0.9630949,0.0004958647,0.03538138,0.00009137337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8669984,0.001229487,0.1306786,0.0003733788,0.00006999708,0.0003010263,0.0001636087,0.00004553598,0.0001399373],"genre_scores_gemma":[0.8251972,0.0001754877,0.1741442,0.0001536925,0.0000449439,0.00003705766,0.0001471871,0.00001032616,0.00008991449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04346557,"threshold_uncertainty_score":0.2908076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02852232415036034,"score_gpt":0.3110554494163246,"score_spread":0.2825331252659643,"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."}}