{"id":"W4406995841","doi":"10.1161/str.56.suppl_1.wp222","title":"Abstract WP222: External Validation of an Automated Hemorrhage Detection and Segmentation Algorithm on Follow-up CT scans in the AcT trial","year":2025,"lang":"en","type":"article","venue":"Stroke","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Foothills Medical Centre; University of Calgary","funders":"","keywords":"Medicine; Segmentation; Algorithm; Radiology; Nuclear medicine; Artificial intelligence","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":[0.07882528,0.00123153,0.001161363,0.0005731417,0.0004277442,0.002183581,0.001768635,0.002113927,0.002157096],"category_scores_gemma":[0.09266879,0.0006202509,0.001454192,0.0004724372,0.001605641,0.001021603,0.001220253,0.001747743,0.001630739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000722566,"about_ca_system_score_gemma":0.001472694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007695071,"about_ca_topic_score_gemma":0.000758304,"domain_scores_codex":[0.9665504,0.02755195,0.001260881,0.002369257,0.002000412,0.0002671167],"domain_scores_gemma":[0.924142,0.04600905,0.007457668,0.01261577,0.008625557,0.001149878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.2768618,0.005868725,0.2440397,0.003828081,0.01214579,0.0009111364,0.001660289,0.1700015,0.03169455,0.00570898,0.04864623,0.1986334],"study_design_scores_gemma":[0.03779566,0.04067993,0.1653216,0.0008866946,0.006708101,0.001967096,0.0003308867,0.657007,0.05031063,0.007615997,0.03089935,0.0004769538],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.867748,0.002542692,0.1057811,0.001391784,0.0005641801,0.004252255,0.007454233,0.002369236,0.007896456],"genre_scores_gemma":[0.9609638,0.0002019761,0.0264722,0.0005433332,0.0001481315,0.002504853,0.007675995,0.0003049981,0.001184733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07882528,"threshold_uncertainty_score":0.4168729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.026609906908344,"score_gpt":0.3094316153091966,"score_spread":0.2828217084008525,"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."}}