{"id":"W2069928976","doi":"10.1364/biomed.2012.btu3a.39","title":"Fast-Fluorescence Camera (FFC) – A Consumer-Grade Digital Camera to Capture Endogenous Tissue Fluorescence","year":2012,"lang":"en","type":"article","venue":"","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"","keywords":"Fluorescence; Flash (photography); Artifact (error); Fluorescence-lifetime imaging microscopy; Digital camera; Computer vision; Computer science; Artificial intelligence; Optics; Physics","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":[0.00133956,0.0005442146,0.0004211961,0.001233471,0.0005804606,0.000619044,0.001215138,0.001423198,0.01144672],"category_scores_gemma":[0.001177643,0.0003485423,0.0003940244,0.0007221454,0.000395192,0.0008851548,0.0003427403,0.0009447842,0.001813751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007859569,"about_ca_system_score_gemma":0.001235115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002770435,"about_ca_topic_score_gemma":0.005257098,"domain_scores_codex":[0.9994249,0.00007407161,0.0000341163,0.0001514626,0.0002645573,0.00005091989],"domain_scores_gemma":[0.9991104,0.0002908399,0.00006493725,0.0001034828,0.0003649129,0.00006535798],"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":[0.0001350912,0.000110988,0.001117244,0.0004037597,0.00002836287,0.0001925944,0.00004504632,0.0006178286,0.8745285,0.002634822,0.01560953,0.1045763],"study_design_scores_gemma":[0.0001012726,0.0007278332,0.009198897,0.00009646218,0.00007328441,0.005467637,0.00006650228,0.02036641,0.8584879,0.001217784,0.1040486,0.0001473275],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09786116,0.004592621,0.8607953,0.001329883,0.0004069737,0.001221367,0.002195119,0.004649265,0.02694842],"genre_scores_gemma":[0.1243901,0.002178548,0.8520052,0.001157607,0.00008726639,0.0007109864,0.001924124,0.0003076889,0.01723851],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01144672,"threshold_uncertainty_score":0.03829306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02231690491462635,"score_gpt":0.2987976460080123,"score_spread":0.276480741093386,"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."}}