{"id":"W3207229599","doi":"10.2147/opth.s337174","title":"ODTiD: Optic Nerve Head SD-OCT Image Dataset","year":2021,"lang":"en","type":"article","venue":"Clinical ophthalmology","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Optical coherence tomography; Optic nerve; Medicine; Optic disc; Ophthalmology; Population; Artificial intelligence; Optic disk; Glaucoma; Optometry; Computer science","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":[0.0005372982,0.00235065,0.001139904,0.00284799,0.0006289117,0.001343882,0.002317383,0.00196364,0.01054301],"category_scores_gemma":[0.001726564,0.0004065312,0.001224132,0.002008642,0.0004291794,0.0007291426,0.001526423,0.0009990042,0.01410396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00101529,"about_ca_system_score_gemma":0.001310238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0132014,"about_ca_topic_score_gemma":0.02629152,"domain_scores_codex":[0.9991428,0.00006832632,0.0001103123,0.0002626732,0.0002883864,0.0001275679],"domain_scores_gemma":[0.9994118,0.00007940543,0.00007642204,0.0001840318,0.0001953945,0.00005301835],"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":[0.0009965098,0.0005296685,0.01146675,0.002514227,0.000337971,0.0009048221,0.00008004764,0.002677312,0.007197198,0.0004827074,0.9047245,0.06808831],"study_design_scores_gemma":[0.001657449,0.0007958165,0.1500863,0.001483752,0.0005412968,0.006983288,0.000621015,0.04486185,0.0218289,0.003153227,0.7674742,0.0005128638],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01475981,0.001048826,0.001534414,0.0001770376,0.0001508158,0.0003609683,0.9750084,0.004509147,0.002450434],"genre_scores_gemma":[0.01154705,0.0002245414,0.002541208,0.00007569579,0.00003293656,0.0003171385,0.9843497,0.00009628666,0.000815488],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0132014,"threshold_uncertainty_score":0.03526992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1253112879893899,"score_gpt":0.4873188260625585,"score_spread":0.3620075380731686,"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."}}