{"id":"W2898641899","doi":"10.1109/embc.2018.8512565","title":"A Spinal Motion Measurement Protocol Utilizing Inertial Sensors Without Magnetometers","year":2018,"lang":"en","type":"article","venue":"","topic":"Scoliosis diagnosis and treatment","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Inertial measurement unit; Pelvis; Trunk; Instrumentation (computer programming); Motion capture; Accelerometer; Rotation (mathematics); Orientation (vector space); Motion (physics); Match moving; Computer science; Physics; Computer vision; Medicine; Mathematics; Anatomy","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":[0.001827034,0.0008949703,0.0007326073,0.001144143,0.0006313397,0.0004820192,0.001035543,0.0007387935,0.003506591],"category_scores_gemma":[0.002167795,0.0003453251,0.0003321015,0.0006232124,0.0004362828,0.0004158195,0.0009210829,0.0005826076,0.001498764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002223375,"about_ca_system_score_gemma":0.001311406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007116731,"about_ca_topic_score_gemma":0.001477401,"domain_scores_codex":[0.997345,0.0006060801,0.0004000115,0.0004466853,0.001109985,0.00009233833],"domain_scores_gemma":[0.9987285,0.00014651,0.0001081594,0.0002340678,0.0006872031,0.00009564047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002342739,0.001743233,0.01705111,0.001017399,0.0001454789,0.0006185284,0.0007194175,0.00359121,0.549849,0.002598274,0.006694301,0.4136294],"study_design_scores_gemma":[0.001777785,0.03517473,0.2736179,0.0005730335,0.0007091511,0.006098215,0.001411508,0.06263954,0.4958732,0.002448169,0.1190613,0.0006154675],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1322799,0.000356716,0.8375156,0.0002320741,0.0003934094,0.01913729,0.001621172,0.001544856,0.006918923],"genre_scores_gemma":[0.2979672,0.0006462621,0.6567472,0.0007226185,0.0002925511,0.03328471,0.002529409,0.0001705416,0.007639564],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003506591,"threshold_uncertainty_score":0.01173073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1064282558797563,"score_gpt":0.3707379867166228,"score_spread":0.2643097308368665,"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."}}