{"id":"W4312115545","doi":"10.1101/2022.12.22.521670","title":"Vessel Metrics: A python based software tool for automated analysis of vascular structure in confocal imaging","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Libin Cardiovascular Institute of Alberta; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Cumming School of Medicine, University of Calgary; Alberta Children's Hospital Research Institute; University of Calgary","keywords":"Software; Computer science; Segmentation; Python (programming language); Vascular network; Consistency (knowledge bases); Artificial intelligence; Computer vision; Data mining; Biology; Anatomy","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":[0.002890407,0.002016376,0.001134924,0.00243356,0.0008368958,0.001812846,0.003098337,0.001054324,0.03508963],"category_scores_gemma":[0.007218292,0.001547545,0.001590769,0.001226104,0.001008045,0.001969111,0.002952063,0.002900957,0.01552658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009015988,"about_ca_system_score_gemma":0.002660326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003666306,"about_ca_topic_score_gemma":0.004782543,"domain_scores_codex":[0.9983851,0.0001801614,0.0002025845,0.0003267452,0.0007666525,0.0001387857],"domain_scores_gemma":[0.9971901,0.001284153,0.0003057891,0.0003905657,0.000647969,0.0001814661],"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":[0.000876602,0.0004094177,0.006739527,0.00217458,0.0006023076,0.0008663199,0.0007112011,0.01974063,0.06373201,0.01648071,0.5800452,0.3076214],"study_design_scores_gemma":[0.0006666933,0.0003202716,0.0144654,0.0005833176,0.0001762488,0.001355614,0.0001719525,0.4797301,0.144501,0.0457353,0.3116522,0.0006419151],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.003130346,0.0001039845,0.5047287,0.000166481,0.000114236,0.0003877661,0.01086778,0.4780834,0.002417258],"genre_scores_gemma":[0.04838497,0.0004191861,0.7420558,0.0008580125,0.0001211732,0.004025532,0.03184451,0.1622404,0.01005043],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03508963,"threshold_uncertainty_score":0.1173865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012242770588972,"score_gpt":0.2580102167139884,"score_spread":0.2478877890080987,"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."}}