{"id":"W3026374798","doi":"10.1016/j.jcjo.2020.03.011","title":"Thresholding strategies to measure vessel density by optical coherence tomography angiography","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Ophthalmology","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Thresholding; Brightness; Contrast (vision); Optical coherence tomography; Segmentation; Nuclear medicine; Artificial intelligence; Medicine; Biomedical engineering; Mathematics; Radiology; Computer science; Optics; Physics; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008795517,0.0005309542,0.000620049,0.001486948,0.000357085,0.001427015,0.0006301744,0.0005790562,0.001315675],"category_scores_gemma":[0.003608704,0.0004673258,0.0003994851,0.001003418,0.000309778,0.0006480943,0.0005910202,0.0004959991,0.0005408814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003304264,"about_ca_system_score_gemma":0.000594047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001814368,"about_ca_topic_score_gemma":0.003339888,"domain_scores_codex":[0.9996784,0.00007726844,0.00002715597,0.00005671137,0.0001189046,0.00004157442],"domain_scores_gemma":[0.9990131,0.0005439636,0.00008463502,0.00009122629,0.0002393748,0.00002764883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003811746,0.0001547617,0.008322535,0.0004090951,0.0001656326,0.0002419102,0.0002610276,0.02507354,0.2935136,0.009499559,0.001958823,0.6600183],"study_design_scores_gemma":[0.00004706215,0.0002676555,0.02674168,0.0001260372,0.0003260159,0.001679329,0.0001896431,0.7132571,0.2345194,0.0157211,0.007022643,0.0001023573],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05506926,0.0008086026,0.9412067,0.0001690456,0.00003097997,0.00006473674,0.0001211097,0.0006319821,0.001897629],"genre_scores_gemma":[0.2939878,0.001017498,0.7027264,0.0001037236,0.00003954457,0.0001111735,0.0002011965,0.0002938536,0.001518713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001814368,"threshold_uncertainty_score":0.004651606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03222208091489268,"score_gpt":0.2798614633127126,"score_spread":0.2476393823978199,"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."}}