{"id":"W2100261848","doi":"10.1109/tbme.2008.2001285","title":"A Fast Quaternion-Based Orientation Optimizer via Virtual Rotation for Human Motion Tracking","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Quaternion; Orientation (vector space); Accelerometer; Computer vision; Rotation (mathematics); Computer science; Magnetometer; Gyroscope; Rate gyro; Artificial intelligence; Match moving; Tracking (education); Motion estimation; Control theory (sociology); Mathematics; Motion (physics); Engineering; Physics; Geometry","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":[0.0009208145,0.0008226219,0.0006958791,0.0003100608,0.0002890313,0.0005481565,0.0004727913,0.0004500086,0.001572931],"category_scores_gemma":[0.001158731,0.0003487071,0.0004336294,0.0004014902,0.0003694936,0.0005278765,0.0005306985,0.0005274895,0.0006078592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003032693,"about_ca_system_score_gemma":0.0006427204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002708458,"about_ca_topic_score_gemma":0.002426006,"domain_scores_codex":[0.9997163,0.0001040883,0.00001835762,0.0000626091,0.00008179866,0.00001684095],"domain_scores_gemma":[0.9997981,0.00006197593,0.00003537822,0.0000312994,0.00006118862,0.0000120481],"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":[0.0001901314,0.00004097063,0.0005236649,0.0001154173,0.00007261438,0.00007707053,0.0001048981,0.6144863,0.01973987,0.01279198,0.003505413,0.3483516],"study_design_scores_gemma":[0.00001613439,0.00005681894,0.0001771728,0.000005974468,0.000008112809,0.00002453371,0.00000646336,0.9942731,0.002589566,0.001187901,0.001644249,0.000009881744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003339559,0.0001322575,0.9956434,0.00003687757,0.00001842457,0.00002000495,0.00001541479,0.000292232,0.0005017964],"genre_scores_gemma":[0.1919993,0.0003273788,0.8048505,0.000061987,0.00005506113,0.0001559768,0.0001320221,0.000177159,0.002240671],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002708458,"threshold_uncertainty_score":0.005385339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009192720105342729,"score_gpt":0.2356220602665813,"score_spread":0.2264293401612386,"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."}}