{"id":"W2156600218","doi":"10.1111/phpp.12161","title":"Real‐time visualization of melanin granules in normal human skin using combined multiphoton and reflectance confocal microscopy","year":2015,"lang":"en","type":"article","venue":"Photodermatology Photoimmunology & Photomedicine","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Coastal Health; Vancouver Coastal Health Research Institute; University of British Columbia; BC Cancer Agency","funders":"Canadian Institutes of Health Research; Canadian Dermatology Foundation","keywords":"Melanin; Confocal microscopy; Human skin; Microscopy; Confocal; Dermis; Autofluorescence; Ex vivo; Materials science; Pathology; In vivo; Optical sectioning; Biomedical engineering; Fluorescence microscope; Staining; Epidermis (zoology); Fluorescence; Chemistry; Anatomy; Optics; Biology; Cell biology; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005403361,0.0004272534,0.0008917212,0.0003964744,0.0001050147,0.000008746503,0.0003774317,0.0006004603,0.00002627674],"category_scores_gemma":[0.0001857155,0.0004454622,0.00006689056,0.0003501165,0.00160428,0.00002607341,0.0002607349,0.0002942795,0.000004236859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009088852,"about_ca_system_score_gemma":0.0001844665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000865976,"about_ca_topic_score_gemma":0.0002060252,"domain_scores_codex":[0.9972882,0.0003547199,0.0009085463,0.0006731837,0.0001796497,0.0005956746],"domain_scores_gemma":[0.9985696,0.00006263373,0.0004430662,0.0005579501,0.0002420723,0.0001246404],"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":[0.001376111,0.0001942452,0.02090213,0.00004313959,0.00005989529,0.00003791417,0.0006007341,0.00000832933,0.9764307,0.00007463696,0.0002429026,0.00002926049],"study_design_scores_gemma":[0.004493751,0.0008978774,0.002329476,0.0001282438,0.0000369347,0.0005336604,0.0002693968,0.0008785789,0.9894614,0.0002769155,0.000328439,0.000365378],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958091,0.001314189,0.001381063,0.00004001663,0.0001673648,0.000821201,0.00002271192,0.00007306787,0.0003712634],"genre_scores_gemma":[0.9915299,0.0006196412,0.006994789,0.0002490833,0.00002368743,0.00009340538,0.0003585917,0.00006734801,0.00006350799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01857265,"threshold_uncertainty_score":0.9997997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343459225723584,"score_gpt":0.3283308559685016,"score_spread":0.3148962637112657,"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."}}