{"id":"W4408201618","doi":"10.3390/app15052830","title":"Models to Identify Small Brain White Matter Hyperintensity Lesions","year":2025,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Hyperintensity; Segmentation; Context (archaeology); White matter; Medicine; Artificial intelligence; Magnetic resonance imaging; Computer science; Pattern recognition (psychology); Radiology","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":[0.000557748,0.0009938509,0.000640509,0.0006518395,0.0002428264,0.0008720791,0.0009759305,0.001358954,0.002235379],"category_scores_gemma":[0.001448549,0.0003575123,0.0009643873,0.0003445599,0.0003149186,0.000676603,0.0005695981,0.001007368,0.0008179683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006652197,"about_ca_system_score_gemma":0.000677456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01174645,"about_ca_topic_score_gemma":0.009353495,"domain_scores_codex":[0.9998259,0.00003066139,0.00001043172,0.00006039507,0.00003959763,0.00003301203],"domain_scores_gemma":[0.999625,0.0001833475,0.00005133325,0.0000197044,0.0001046921,0.00001582891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001530848,0.00008225481,0.002730975,0.00009240011,0.0001038001,0.0001051006,0.0000555851,0.9186487,0.003960963,0.003052119,0.002486636,0.06852841],"study_design_scores_gemma":[0.000003766703,0.00001761269,0.0002609304,0.000006404709,0.000009554918,0.00001746939,0.00000397652,0.9980716,0.0003716089,0.0009252562,0.0003087159,0.000003238149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1505803,0.003870699,0.8305668,0.001331686,0.0003333002,0.000189155,0.0009797734,0.003115294,0.009032929],"genre_scores_gemma":[0.9090845,0.001367572,0.07195932,0.0003940264,0.0001632636,0.0002363472,0.001292924,0.000134843,0.01536714],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01174645,"threshold_uncertainty_score":0.0233562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0977056648071548,"score_gpt":0.3142707164477433,"score_spread":0.2165650516405885,"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."}}