{"id":"W2064255267","doi":"10.1364/ol.38.002786","title":"System and methods for wide-field quantitative fluorescence imaging during neurosurgery","year":2013,"lang":"en","type":"article","venue":"Optics Letters","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; University of Toronto; University Health Network","funders":"National Institute of Neurological Disorders and Stroke; Norris Cotton Cancer Center; National Institutes of Health","keywords":"Optics; Hyperspectral imaging; Fluorophore; Fluorescence; Materials science; Fluorescence-lifetime imaging microscopy; Absorption (acoustics); Point spread function; Dynamic range; Scattering; Biomedical engineering; Physics; Computer science; Medicine; Artificial intelligence","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":[0.0001373022,0.0001626813,0.0001878951,0.00008865524,0.00008692382,0.000107033,0.00009919574,0.00003521847,0.000003486502],"category_scores_gemma":[0.0001183609,0.0001661299,0.00005159039,0.00009118065,0.00003772257,0.0002874014,0.00002743343,0.0001229788,0.000008610867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006279064,"about_ca_system_score_gemma":0.000004944366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001127773,"about_ca_topic_score_gemma":3.607474e-7,"domain_scores_codex":[0.9992108,0.0000142946,0.0002178664,0.0001691162,0.00007435715,0.0003135107],"domain_scores_gemma":[0.9989439,0.0007324241,0.00003814645,0.000175162,0.00003621459,0.00007412986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001036302,0.000002460738,0.0009110615,0.0004602521,0.00003739321,0.000007454999,0.0002025379,0.001705013,0.9909002,0.0005260039,0.0006643081,0.004572907],"study_design_scores_gemma":[0.0007889411,0.00004566637,0.002149134,0.000323606,0.00007420401,0.00004562414,0.0004632556,0.6349825,0.3593762,0.00024264,0.0007820242,0.0007262978],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5036027,0.0002908901,0.493922,0.0005110648,0.0008930814,0.0003844738,0.00000493367,0.0002510591,0.0001397557],"genre_scores_gemma":[0.6667818,0.00005010692,0.3323798,0.000513316,0.00007462261,0.0001025137,0.000002402667,0.00008052835,0.00001487366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6332774,"threshold_uncertainty_score":0.677458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009006743840271073,"score_gpt":0.2503775466155199,"score_spread":0.2413708027752488,"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."}}