{"id":"W2510908842","doi":"10.3389/fninf.2016.00037","title":"AxonSeg: Open Source Software for Axon and Myelin Segmentation and Morphometric Analysis","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Université Laval; Institut Universitaire en Santé Mentale de Québec; Polytechnique Montréal","funders":"Fonds de Recherche du Québec - Santé; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Axon; Segmentation; Artificial intelligence; Computer science; Myelin; Pattern recognition (psychology); Image segmentation; Graphical user interface; Software; Image processing; Computer vision; Anatomy; Neuroscience; Biology; Image (mathematics); Central nervous system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001030113,0.001763399,0.0009923365,0.001998137,0.000437673,0.001196319,0.001760844,0.00106081,0.05918343],"category_scores_gemma":[0.002357417,0.001228072,0.00139637,0.0009754536,0.0003509344,0.00149097,0.002172247,0.001318606,0.03552284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004758346,"about_ca_system_score_gemma":0.001303827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001492241,"about_ca_topic_score_gemma":0.002992216,"domain_scores_codex":[0.9995034,0.00005482888,0.00007080736,0.0001228757,0.0001900448,0.00005808058],"domain_scores_gemma":[0.9994059,0.0002308817,0.00008352163,0.00008533993,0.0001525098,0.0000418501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009382109,0.0001294402,0.003079878,0.00389021,0.0004210751,0.0006505963,0.0005505799,0.007786328,0.06720091,0.008078946,0.5439743,0.3632996],"study_design_scores_gemma":[0.000322916,0.0002416628,0.01058252,0.0009214631,0.0002770947,0.002930393,0.0001799819,0.07958279,0.09960645,0.02046352,0.784494,0.0003971834],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.007161088,0.001479802,0.4426819,0.0002250773,0.0002368002,0.0003282754,0.04125768,0.4964341,0.01019542],"genre_scores_gemma":[0.03819793,0.00174947,0.6675746,0.0007910866,0.0001177627,0.002987867,0.08509768,0.1772287,0.02625487],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.05918343,"threshold_uncertainty_score":0.1979883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008734298136995113,"score_gpt":0.2542633862635632,"score_spread":0.2455290881265681,"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."}}