{"id":"W4240500344","doi":"10.34133/2020/8620932","title":"Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning","year":2020,"lang":"en","type":"article","venue":"BME Frontiers","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; University of California, San Diego; National Institutes of Health","keywords":"Artificial intelligence; Computer science; Segmentation; Deep learning; Algorithm; Machine learning; Pattern recognition (psychology)","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":[],"consensus_categories":[],"category_scores_codex":[0.000147423,0.0001360839,0.0002418465,0.00005074643,0.00002650284,0.00001752506,0.0001891017,0.0001278063,0.0000117072],"category_scores_gemma":[0.00009001168,0.0001474241,0.0001410411,0.0001650869,0.00004362606,0.000006387678,0.00008740325,0.0001670985,0.000001094389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001956741,"about_ca_system_score_gemma":0.00002465909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001453838,"about_ca_topic_score_gemma":0.00002608476,"domain_scores_codex":[0.9990073,0.00007939453,0.000237653,0.000359074,0.0001029963,0.000213523],"domain_scores_gemma":[0.9996127,0.000002783061,0.00006766724,0.0001964167,0.00004267575,0.00007775061],"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":[0.00005562541,0.00002291682,0.006825756,0.0000159136,0.00005598773,0.000002556514,0.00008256741,0.01548356,0.9415681,0.0000025701,0.03551069,0.000373713],"study_design_scores_gemma":[0.0004669208,0.00005455061,0.00001523345,0.000006839012,0.00002328031,9.467784e-7,0.0001090501,0.3477516,0.6344345,0.00002900287,0.01693844,0.0001696325],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7443355,0.004776977,0.2501338,0.000190628,0.00001746184,0.000139132,0.000003029301,0.00002365305,0.0003798476],"genre_scores_gemma":[0.9741994,0.0003319241,0.02432078,0.0006463882,0.00005370339,0.00001031688,0.0002132873,0.00002992106,0.0001942724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.332268,"threshold_uncertainty_score":0.6011782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005135031631508179,"score_gpt":0.253844566407582,"score_spread":0.2487095347760738,"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."}}