{"id":"W1992817665","doi":"10.1118/1.2143352","title":"Coronary x‐ray angiographic reconstruction and image orientation","year":2006,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Ottawa; Natural Resources Canada","funders":"","keywords":"Epipolar geometry; Imaging phantom; Computer vision; Artificial intelligence; Iterative reconstruction; Coronary arteries; Orientation (vector space); Computer science; 3D reconstruction; Surface reconstruction; Intersection (aeronautics); Mathematics; Artery; Radiology; Geometry; Medicine; Image (mathematics); Surface (topology); Surgery","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":[0.0007840662,0.0003807763,0.000384898,0.0005814708,0.0001476935,0.0007468061,0.0007173301,0.0004862297,0.002016133],"category_scores_gemma":[0.00194165,0.0004966354,0.0004135782,0.0003653878,0.0003219711,0.0003100945,0.0005101947,0.0005441404,0.0005059313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002862293,"about_ca_system_score_gemma":0.0005787787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001381432,"about_ca_topic_score_gemma":0.001713154,"domain_scores_codex":[0.9995763,0.00009891977,0.00002025395,0.00007009714,0.0002077728,0.00002662476],"domain_scores_gemma":[0.9995571,0.0001625476,0.00005602596,0.0001248809,0.00007977884,0.00001960543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003165734,0.0001134289,0.005758272,0.0002159698,0.0001086126,0.0005368395,0.0002521841,0.1756099,0.396651,0.0114359,0.001930805,0.4070705],"study_design_scores_gemma":[0.00008853238,0.0003216462,0.008290607,0.00004173873,0.00007550236,0.005076496,0.00005078898,0.7533651,0.2133802,0.003530729,0.01565945,0.0001192407],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0211698,0.0001048793,0.977119,0.00006267812,0.00000922379,0.00002389222,0.00005378899,0.000744506,0.0007121471],"genre_scores_gemma":[0.1627477,0.0002137101,0.835699,0.00002838759,0.00001200495,0.00006056892,0.0001050306,0.0002039839,0.0009297043],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002016133,"threshold_uncertainty_score":0.006744623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005944186327397969,"score_gpt":0.2478548343528575,"score_spread":0.2419106480254596,"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."}}