{"id":"W2735957153","doi":"10.3389/fnins.2017.00381","title":"Age and Glaucoma-Related Characteristics in Retinal Nerve Fiber Layer and Choroid: Localized Morphometrics and Visualization Using Functional Shapes Registration","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Glaucoma and retinal disorders","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Canadian Institutes of Health Research; Fondation pour la Recherche sur Alzheimer; Michael Smith Health Research BC; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Nerve fiber layer; Morphometrics; Glaucoma; Choroid; Retinal; Visualization; Ophthalmology; Nerve fiber; Anatomy; Retina; Biology; Medicine; Neuroscience; Artificial intelligence; Computer science; Zoology","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":[0.000402699,0.0003241854,0.0001535577,0.001294522,0.0001101927,0.0003714068,0.000158557,0.0002720778,0.0007167024],"category_scores_gemma":[0.0007317467,0.000152285,0.0003292374,0.0005601763,0.0002424602,0.0003814141,0.0003546008,0.0002002965,0.0001341512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001635107,"about_ca_system_score_gemma":0.0002561866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001308828,"about_ca_topic_score_gemma":0.001643818,"domain_scores_codex":[0.9998876,0.00002451788,0.000006532626,0.00003266269,0.00003439366,0.00001423157],"domain_scores_gemma":[0.9998202,0.00003967421,0.000057786,0.0000336984,0.00003096411,0.0000177419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006561056,0.00008888308,0.0437443,0.0003253655,0.0001708023,0.0006712315,0.001206909,0.03548744,0.617534,0.005604765,0.001446193,0.293064],"study_design_scores_gemma":[0.00003422935,0.0004053391,0.4179502,0.0001011484,0.0002056366,0.002841103,0.00069904,0.3407791,0.2198204,0.008958958,0.008011682,0.0001931568],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8500656,0.0006918563,0.1464873,0.0001097974,0.00001931289,0.00004164897,0.0004542255,0.0006215278,0.001508712],"genre_scores_gemma":[0.9321167,0.0005024437,0.06593176,0.00001859267,0.00001629803,0.00005084279,0.0003617481,0.000120863,0.0008806803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001308828,"threshold_uncertainty_score":0.002602339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02891007834555651,"score_gpt":0.2839065815382957,"score_spread":0.2549965031927392,"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."}}