{"id":"W4251405356","doi":"10.22215/etd/2016-11324","title":"Prediction of Human Postural Response in Shipboard Environments Using Multibody Dynamics and Sensory-Based Control","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Motion capture; Pendulum; Multibody system; Simulation; Engineering; Motion (physics); Inverted pendulum; Vestibular system; Control theory (sociology); Computer science; Artificial intelligence; Control (management); Psychology; Nonlinear system","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":[0.0001070502,0.0003054447,0.0002091938,0.0001737799,0.0001268385,0.0003077489,0.0001384074,0.0001994385,0.0006258696],"category_scores_gemma":[0.0005890162,0.0001569873,0.0002334079,0.00009848247,0.0001267954,0.0002378334,0.0001831511,0.0001644368,0.0001443444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001613441,"about_ca_system_score_gemma":0.0002226602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005369705,"about_ca_topic_score_gemma":0.005619631,"domain_scores_codex":[0.9999549,0.000008934395,0.000002619111,0.00001173351,0.00001605848,0.000005665086],"domain_scores_gemma":[0.9999175,0.00003848934,0.00001318726,0.000006973824,0.00001834786,0.000005437086],"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":[0.0001610293,0.0001047359,0.009559033,0.000140964,0.00006778172,0.0001116442,0.0001741872,0.8618166,0.05237548,0.0008237647,0.0003204624,0.07434421],"study_design_scores_gemma":[0.00000510342,0.00007406532,0.008009466,0.000007063094,0.000005894641,0.00001357275,0.00001787207,0.9895746,0.001926619,0.0002505428,0.0001097908,0.000005424766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.70612,0.000204103,0.2904818,0.00009201022,0.00001971423,0.00007559949,0.0001661726,0.0002442491,0.002596451],"genre_scores_gemma":[0.9922804,0.00009657656,0.007134882,0.000004556386,0.000003841101,0.00002847038,0.0000486027,0.000004567393,0.0003982891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005369705,"threshold_uncertainty_score":0.01067686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01051366397928184,"score_gpt":0.2409909271778378,"score_spread":0.2304772631985559,"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."}}