{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009327529,0.0007898645,0.0004022976,0.0007890005,0.0003042931,0.0005754333,0.0006638353,0.0007825173,0.0009826219],"category_scores_gemma":[0.0005069425,0.0004010274,0.0003047004,0.0003759481,0.000519196,0.0007229114,0.0005909303,0.0006995418,0.0004502203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00045195,"about_ca_system_score_gemma":0.0002704879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002195963,"about_ca_topic_score_gemma":0.0007723777,"domain_scores_codex":[0.9992823,0.0001348881,0.00004278254,0.0002699215,0.0002178561,0.00005230072],"domain_scores_gemma":[0.9996706,0.0001105151,0.00007272056,0.00005142369,0.00006392121,0.0000308913],"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":[0.00003431191,0.00002299918,0.0001235395,0.00006237991,0.000007474798,0.00003163489,0.00004105012,0.0001652894,0.9937017,0.0002986131,0.00006202835,0.00544897],"study_design_scores_gemma":[0.000004705116,0.00008052854,0.0004060262,0.000006543637,0.0000122448,0.0001158691,0.00002173196,0.005978349,0.991658,0.0002130726,0.001490959,0.00001181309],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.333936,0.003830554,0.6569686,0.0002718977,0.0002401089,0.0003287882,0.0002850588,0.001146893,0.002992118],"genre_scores_gemma":[0.4618977,0.002440919,0.5307878,0.0002876444,0.00007627642,0.000501461,0.0002604531,0.00008013998,0.00366766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009826219,"threshold_uncertainty_score":0.00493294,"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."}}