{"id":"W2617538694","doi":"10.1149/ma2010-01/19/1057","title":"Using Fluorescence Lifetime Imaging Microscopy to Monitor Photofrin Uptake, Redistribution, and Intracellular Microenvironment","year":2010,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Redistribution (election); Microscopy; Intracellular; Fluorescence microscope; Fluorescence-lifetime imaging microscopy; Fluorescence; Biophysics; Chemistry; Materials science; Nanotechnology; Medicine; Optics; Biology; Pathology; Physics; Biochemistry; Political science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004187402,0.0003065867,0.0001918862,0.00006238281,0.0002509266,0.00009654083,0.0002816422,0.0001796815,0.000008131439],"category_scores_gemma":[0.0003349461,0.0003444787,0.00005256683,0.00009270212,0.0002193298,0.00001591867,0.0002648032,0.0003556703,0.00001563863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004759458,"about_ca_system_score_gemma":0.00004314389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006452174,"about_ca_topic_score_gemma":0.000006230043,"domain_scores_codex":[0.9981486,0.00003109453,0.0004164323,0.0006940239,0.0001685937,0.0005412846],"domain_scores_gemma":[0.9989579,0.00001642532,0.0001824036,0.000499499,0.00007817599,0.0002655683],"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":[0.00004131117,0.00004834194,0.002632954,0.00001617565,0.000008304005,0.00001445069,0.00004501974,0.0001963839,0.9954711,0.000001367656,0.0005244918,0.001000061],"study_design_scores_gemma":[0.0001869425,0.00005211153,0.003457115,0.00009682841,0.00001503944,0.00005749018,0.0000487619,0.0001848688,0.983486,0.00002790825,0.01204029,0.0003466357],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951561,0.0004589256,0.003023375,0.0001517221,0.0002998758,0.0003817633,0.00004643462,0.00006725369,0.0004145152],"genre_scores_gemma":[0.7534544,0.00004712976,0.2459656,0.0001076552,0.000279748,0.00001605578,0.00004578311,0.00004475809,0.00003884665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2429422,"threshold_uncertainty_score":0.9999007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007192285579185108,"score_gpt":0.2673604255570982,"score_spread":0.2601681399779131,"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."}}