{"id":"W2083745515","doi":"10.1117/12.770331","title":"2D/3D registration with the CMA-ES method","year":2008,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Artificial intelligence; Kalman filter; Computer vision; Maxima and minima; Transformation (genetics); Simplex; Computation; Image registration; Imaging phantom; Algorithm; Image (mathematics); Mathematics","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":[0.001323723,0.0008556361,0.0006988391,0.001432818,0.0004311752,0.001258424,0.001250203,0.001091661,0.003322475],"category_scores_gemma":[0.00293978,0.0005000207,0.001035842,0.001238466,0.0006471783,0.001468492,0.001623993,0.001303528,0.002319446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004336394,"about_ca_system_score_gemma":0.001116561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002330728,"about_ca_topic_score_gemma":0.003031856,"domain_scores_codex":[0.9978753,0.0003426771,0.0001123284,0.0003720587,0.001225681,0.0000719582],"domain_scores_gemma":[0.9987081,0.0003127495,0.0001327794,0.0004045755,0.0003856736,0.00005612104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001965166,0.0001101769,0.001330215,0.0001975644,0.0001573859,0.0001681771,0.0001988978,0.05752845,0.07905102,0.009982555,0.004243182,0.8468358],"study_design_scores_gemma":[0.00003368958,0.00008806496,0.001245221,0.00002023214,0.00003437667,0.0006122824,0.0000479898,0.9220614,0.05518118,0.002670185,0.01793231,0.00007299679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002370389,0.00008708401,0.9958842,0.00004154041,0.0000500772,0.00003373647,0.00002775733,0.0008651751,0.0006399803],"genre_scores_gemma":[0.04213058,0.0001197801,0.955681,0.0000695012,0.00003580773,0.00007179185,0.0001302693,0.0002994695,0.001461867],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003322475,"threshold_uncertainty_score":0.01111484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01284800818361125,"score_gpt":0.2337165615781537,"score_spread":0.2208685533945425,"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."}}