{"id":"W2460803088","doi":"10.1007/978-3-319-31808-0_9","title":"Left Atrial Wall Segmentation from CT for Radiofrequency Catheter Ablation Planning","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Atrial Fibrillation Management and Outcomes","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Catheter; Ablation; Segmentation; Catheter ablation; Computer vision; Radiofrequency ablation; Artificial intelligence; Radiology; Medicine; Cardiology","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":[0.0002625598,0.00063618,0.0003040133,0.0009027859,0.0001475146,0.001066153,0.0005465973,0.0007037045,0.004934404],"category_scores_gemma":[0.001127944,0.0005334134,0.0006403344,0.0005553915,0.0001637803,0.0005302393,0.000481142,0.0006619081,0.00242685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000202885,"about_ca_system_score_gemma":0.0003758141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001213902,"about_ca_topic_score_gemma":0.002094519,"domain_scores_codex":[0.9999261,0.00001373371,0.00000707829,0.00001647398,0.00002843059,0.000008194705],"domain_scores_gemma":[0.9997223,0.000183192,0.00001650795,0.00002584942,0.00003770521,0.00001442642],"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":[0.0001369129,0.00003019866,0.001248869,0.0003968349,0.00005012879,0.0008185158,0.0001229878,0.0400942,0.0761891,0.003762904,0.01978503,0.8573642],"study_design_scores_gemma":[0.00005124173,0.0001899612,0.007695238,0.0007233314,0.0002302308,0.009497313,0.0001364095,0.7487309,0.11339,0.0230855,0.09613439,0.0001354667],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01495927,0.005705118,0.964834,0.000594323,0.000241123,0.0001364769,0.0007437609,0.002752875,0.01003299],"genre_scores_gemma":[0.1357188,0.007734293,0.8422399,0.0004138004,0.0003680936,0.0001561022,0.001870291,0.001596239,0.009902587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004934404,"threshold_uncertainty_score":0.01650721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04981124032823282,"score_gpt":0.3196497859117863,"score_spread":0.2698385455835535,"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."}}