{"id":"W4402307941","doi":"10.18280/ts.410445","title":"Digital Subtraction Angiography Generation with Deep Decoupling Network","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Decoupling (probability); Digital subtraction angiography; Subtraction; Computer science; Artificial intelligence; Computer vision; Angiography; Radiology; Medicine; Mathematics; Arithmetic; Engineering","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":[0.0001614203,0.0004038171,0.000213554,0.0002997463,0.0001784264,0.0002664634,0.0004041022,0.0003205274,0.003466439],"category_scores_gemma":[0.0002544035,0.0001891593,0.0001749973,0.0002695768,0.0001132952,0.0004404408,0.0005995101,0.0003851013,0.0009110768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001811025,"about_ca_system_score_gemma":0.0003452312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005627759,"about_ca_topic_score_gemma":0.001581273,"domain_scores_codex":[0.9999219,0.00001422145,0.000003059077,0.00001967285,0.0000306851,0.00001046521],"domain_scores_gemma":[0.9998994,0.00002789468,0.000007984838,0.00002052839,0.0000315171,0.00001269836],"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":[0.0003744757,0.0001663784,0.001836166,0.0001246999,0.00005678844,0.0003098777,0.00007724192,0.02214265,0.3888594,0.008404137,0.006105111,0.5715432],"study_design_scores_gemma":[0.00007753215,0.0002988206,0.002980037,0.00002698979,0.00009987886,0.001408686,0.00003495014,0.7675483,0.1993247,0.008013382,0.0201186,0.00006821457],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03277795,0.0002334059,0.9596426,0.0002237201,0.00005993926,0.0000501423,0.0001667228,0.0008442136,0.006001242],"genre_scores_gemma":[0.5169618,0.0004142186,0.4688086,0.0003309636,0.00006967727,0.0000944726,0.0006458611,0.0001442559,0.01253018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003466439,"threshold_uncertainty_score":0.01159638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006395729976121775,"score_gpt":0.1817333421218666,"score_spread":0.1753376121457448,"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."}}