{"id":"W4411350308","doi":"10.1016/j.xops.2025.100852","title":"Automated Segmentation of Subretinal Fluid from OCT: A Vision Transformer Approach with Cross-Validation","year":2025,"lang":"en","type":"article","venue":"Ophthalmology Science","topic":"Retinal and Macular Surgery","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; University of Ottawa; Artificial Intelligence in Medicine (Canada); University of Toronto","funders":"","keywords":"Optical coherence tomography; Segmentation; Computer vision; Artificial intelligence; Tomography; Computer science; Transformer; Optics; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00766157,0.001485037,0.001402492,0.002694469,0.0007601131,0.001324819,0.001991209,0.002065427,0.001267769],"category_scores_gemma":[0.007204783,0.000764115,0.002198357,0.0009904773,0.0008011105,0.001002333,0.00185142,0.00159958,0.0009553391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001271399,"about_ca_system_score_gemma":0.001603656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005886733,"about_ca_topic_score_gemma":0.005376091,"domain_scores_codex":[0.9976406,0.0007189066,0.0002377981,0.000787612,0.0004173097,0.0001976681],"domain_scores_gemma":[0.9965653,0.001404295,0.0004021818,0.0004956455,0.001003609,0.0001290291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008804271,0.0006056142,0.02077444,0.000234236,0.0008039774,0.0003555365,0.0002896771,0.3026195,0.03029034,0.0009593541,0.00300788,0.639179],"study_design_scores_gemma":[0.00001641613,0.0001444343,0.002476541,0.00001679636,0.00004399192,0.0001296654,0.00002250677,0.9916032,0.004647116,0.0005593268,0.0003265766,0.00001351312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1402252,0.001029473,0.8526458,0.0002110761,0.00006147013,0.000328166,0.0002920312,0.004424294,0.000782573],"genre_scores_gemma":[0.6542929,0.0002682421,0.3411525,0.0003286007,0.00004712927,0.0003474129,0.001767855,0.0003786126,0.001416763],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00766157,"threshold_uncertainty_score":0.0405187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01420593441767644,"score_gpt":0.348304118356801,"score_spread":0.3340981839391246,"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."}}