{"id":"W4393082008","doi":"10.1016/j.stem.2024.02.011","title":"Autofluorescence is a biomarker of neural stem cell activation state","year":2024,"lang":"en","type":"article","venue":"Cell stem cell","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; College of Engineering, University of Wisconsin-Madison; National Heart, Lung, and Blood Institute; American Foundation for Aging Research; University of Wisconsin-Madison; McGill University; Vallee Foundation; National Cancer Institute; National Institutes of Health; American Federation for Aging Research","keywords":"Autofluorescence; Neural stem cell; Biology; Neurogenesis; Cell biology; Cell; Stem cell; Live cell imaging; Cell fate determination; Fluorescence-lifetime imaging microscopy; Fluorescence; Neuroscience; Biochemistry; Transcription factor; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003728934,0.000352664,0.00025298,0.0008846477,0.000425117,0.0005269138,0.0002938392,0.0004937873,0.002309771],"category_scores_gemma":[0.0002831886,0.0002362693,0.0002435951,0.0004475304,0.0004836155,0.0005764584,0.000312911,0.0008464277,0.0004447626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004954481,"about_ca_system_score_gemma":0.0003251034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001238104,"about_ca_topic_score_gemma":0.00185618,"domain_scores_codex":[0.9997763,0.00003336774,0.00001164101,0.00005803348,0.00007018041,0.00005044792],"domain_scores_gemma":[0.999668,0.000114576,0.00006070061,0.00002917237,0.00007339621,0.00005416399],"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":[0.00009016178,0.00003179767,0.002277979,0.00003698507,0.00001539955,0.00006950484,0.00004926822,0.00004954428,0.9940988,0.0005325735,0.0001016065,0.002646385],"study_design_scores_gemma":[0.000008281973,0.0001747634,0.03663949,0.00001086041,0.00003348884,0.0004269014,0.0001073546,0.001077235,0.9588371,0.0005117466,0.002161127,0.0000117478],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9518189,0.003031994,0.03515992,0.0002552379,0.00006580492,0.00005117547,0.0005685798,0.0004001605,0.00864813],"genre_scores_gemma":[0.9778517,0.001833439,0.01250849,0.0001295875,0.00005484748,0.00009848549,0.0006917223,0.00006513318,0.00676653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002309771,"threshold_uncertainty_score":0.007726967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01072882397213012,"score_gpt":0.2570450448935428,"score_spread":0.2463162209214127,"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."}}