{"id":"W1986624256","doi":"10.1115/1.4000109","title":"Accuracy of Inertial Motion Sensors in Static, Quasistatic, and Complex Dynamic Motion","year":2009,"lang":"en","type":"article","venue":"Journal of Biomechanical Engineering","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Laurentian University","funders":"Workplace Safety and Insurance Board","keywords":"Quasistatic process; Physics; Orientation (vector space); Motion (physics); Inertial frame of reference; Range (aeronautics); Planar; Inertial measurement unit; Acoustics; Computer science; Mathematics; Computer vision; Classical mechanics; Engineering; Geometry; Computer graphics (images)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002157654,0.0001249264,0.0002847034,0.0003169277,0.00001092377,0.00001460478,0.00006645857,0.00008029532,0.000008463592],"category_scores_gemma":[0.0001440226,0.0001204437,0.00006001863,0.0002757878,0.000009145122,0.0002094413,0.000007063687,0.0002017131,8.052166e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009360461,"about_ca_system_score_gemma":0.000004770184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007304019,"about_ca_topic_score_gemma":0.000002202749,"domain_scores_codex":[0.9989183,0.00002047444,0.0006317406,0.00007279226,0.0001931686,0.0001635065],"domain_scores_gemma":[0.9995782,0.00008507435,0.000125906,0.00006927108,0.00006480672,0.00007668779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002918168,0.00003492699,0.000009654857,0.00007320364,0.00001424433,0.00001153075,0.0001261321,0.1634184,0.8066079,0.0002376075,0.000007048469,0.02943016],"study_design_scores_gemma":[0.0007363708,0.0001864796,0.007041425,0.0001217207,0.00001955569,0.00005101194,0.0000399993,0.9346471,0.05676134,0.00022698,0.0000354568,0.0001325889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8758078,0.0001192184,0.1236166,0.0001090461,0.0002292126,0.0000733843,0.000003688714,0.0000307015,0.00001036921],"genre_scores_gemma":[0.9950816,0.0001207678,0.004708981,0.00000935126,0.00005812707,4.280589e-7,0.000005044049,0.0000146461,0.00000104076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7712287,"threshold_uncertainty_score":0.491155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00913077041768911,"score_gpt":0.238807029250724,"score_spread":0.2296762588330349,"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."}}