{"id":"W1989015785","doi":"10.1117/1.3523369","title":"Topographic mapping of subsurface fluorescent structures in tissue using multiwavelength excitation","year":2010,"lang":"en","type":"article","venue":"Journal of Biomedical Optics","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Ontario Institute for Cancer Research; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health; National Institute of Neurological Disorders and Stroke; Ontario Ministry of Health and Long-Term Care","keywords":"Imaging phantom; Fluorescence; Protoporphyrin IX; Optics; Materials science; Wavelength; Excitation; Scattering; Excitation wavelength; Light scattering; Absorption (acoustics); Biomedical engineering; 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":[0.0001476159,0.000325904,0.0001780585,0.0004485274,0.0001395082,0.00046698,0.0002894507,0.0003851841,0.0004625976],"category_scores_gemma":[0.0005642839,0.0002227064,0.0001658521,0.0002866173,0.0002504636,0.0004778682,0.0004430833,0.0003237132,0.0001713683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003863681,"about_ca_system_score_gemma":0.0002956021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005862617,"about_ca_topic_score_gemma":0.001315635,"domain_scores_codex":[0.9999158,0.00001053791,0.000002921999,0.00002226652,0.00003913381,0.00000930258],"domain_scores_gemma":[0.9997669,0.00008555046,0.00005846868,0.00003263076,0.00004136997,0.00001512011],"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":[0.00009300348,0.00002765444,0.001214574,0.00005726577,0.000009317318,0.00008836585,0.00009212453,0.01737642,0.9336573,0.001037996,0.0001126135,0.04623328],"study_design_scores_gemma":[0.00001786662,0.0001730542,0.004862288,0.00001156558,0.00001867861,0.0008226415,0.00006090814,0.3322374,0.6590567,0.001397131,0.001301363,0.00004046984],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4763086,0.0003197461,0.5214235,0.0001109174,0.00001307632,0.00002819249,0.00008605891,0.000516218,0.001193728],"genre_scores_gemma":[0.6250246,0.0003208343,0.3734714,0.00002466701,0.000009057158,0.00002750948,0.00007435412,0.00005571459,0.0009917652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0005862617,"threshold_uncertainty_score":0.002803326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0191939433712598,"score_gpt":0.3384834479499572,"score_spread":0.3192895045786974,"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."}}