{"id":"W2765880105","doi":"10.1177/0954411917735556","title":"Single-camera visual odometry to track a surgical X-ray C-arm base","year":2017,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of British Columbia","funders":"","keywords":"Artificial intelligence; Computer vision; Visual odometry; Odometry; Orientation (vector space); Computer science; Monocular; Homography; Optical flow; Frame (networking); Base (topology); Robot; Mathematics; Mobile robot; Image (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":[0.0002652199,0.0007024231,0.000541943,0.0009427826,0.0002828039,0.0005952042,0.0007982501,0.0004359172,0.001696574],"category_scores_gemma":[0.000928802,0.000363404,0.0003559926,0.0006820919,0.0001755352,0.0005099083,0.0008657715,0.0005105462,0.0007652941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003151895,"about_ca_system_score_gemma":0.001167873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004047289,"about_ca_topic_score_gemma":0.007043033,"domain_scores_codex":[0.9997113,0.00002212779,0.0000132381,0.00006012639,0.0001644892,0.00002865469],"domain_scores_gemma":[0.9996578,0.00003979671,0.00006204399,0.00006554552,0.0001485804,0.0000261747],"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":[0.0002261687,0.0001027115,0.004685572,0.000401333,0.00009760467,0.0002340066,0.0002204938,0.08641473,0.1741569,0.002843372,0.003046428,0.7275708],"study_design_scores_gemma":[0.00004097138,0.0005101215,0.009233099,0.0001045543,0.00007349558,0.0008123346,0.0001355627,0.9008407,0.07582448,0.001521567,0.01083773,0.00006543081],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02896191,0.000377099,0.9670041,0.00005536844,0.00008395797,0.00008457459,0.0001105005,0.001019781,0.002302557],"genre_scores_gemma":[0.6100039,0.0007326677,0.3848514,0.00007188431,0.000057389,0.0001555612,0.0002958131,0.00009082964,0.003740445],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004047289,"threshold_uncertainty_score":0.008047462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02253445852213256,"score_gpt":0.2534265092901979,"score_spread":0.2308920507680654,"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."}}