{"id":"W4386472840","doi":"10.1109/tim.2023.3312484","title":"Tracking-by-Registration: A Robust Approach for Optical Tracking System in Surgical Navigation","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Basic and Applied Basic Research Foundation of Guangdong Province","keywords":"Tracking (education); Computer vision; Computer science; Artificial intelligence; Metric (unit); Tracking system; Reliability (semiconductor); Line-of-sight; Kalman filter; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004107826,0.0001517299,0.0001503223,0.000168183,0.0001394701,0.00009131582,0.00004040853,0.00009771995,0.000004009283],"category_scores_gemma":[0.000002974382,0.0001638499,0.00005264054,0.0003194934,0.00002401315,0.0001709261,2.823932e-7,0.0001192943,0.000003801726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002955052,"about_ca_system_score_gemma":0.00002012058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001145491,"about_ca_topic_score_gemma":0.00001828054,"domain_scores_codex":[0.9987875,0.00002846735,0.0003709103,0.0002271147,0.0003837451,0.0002023024],"domain_scores_gemma":[0.999685,0.00003086419,0.00003457659,0.00009008042,0.00008273756,0.0000767172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005412519,0.00007829133,0.00001948359,0.0002714978,0.00002772783,0.000002706619,0.0002324107,0.9610369,0.004345484,0.0004916703,0.0000840107,0.03335571],"study_design_scores_gemma":[0.001850651,0.0000970312,0.0001518546,0.0001421661,0.00003752843,0.00001642487,0.001039024,0.9526244,0.04358699,0.00001245651,0.0002238827,0.0002175565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08940956,0.00002369777,0.9088743,0.00005876953,0.0003395848,0.0005965638,0.00002329056,0.0002660101,0.0004082579],"genre_scores_gemma":[0.9977545,0.00003554458,0.001793167,0.00001017195,0.00003343548,0.0002152085,0.0001092123,0.00002770785,0.00002103952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9083449,"threshold_uncertainty_score":0.6681604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05553657396997353,"score_gpt":0.2486781654818226,"score_spread":0.1931415915118491,"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."}}