{"id":"W2007836338","doi":"10.1007/s11517-011-0736-0","title":"Quasi real-time gait event detection using shank-attached gyroscopes","year":2011,"lang":"en","type":"article","venue":"Medical & Biological Engineering & Computing","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":122,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Gyroscope; Gait; Accelerometer; Robustness (evolution); Computer science; Event (particle physics); Artificial intelligence; Acceleration; Step detection; Computer vision; Gait analysis; Algorithm; Engineering; Physical medicine and rehabilitation; Physics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004913302,0.0003023456,0.0004281907,0.0001539079,0.00009690511,0.00003009267,0.00025112,0.0003185455,0.00148866],"category_scores_gemma":[0.0002975856,0.0002551479,0.0001970234,0.0003994794,0.00005340403,0.00006070066,0.0001005419,0.0004395573,0.0002426614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009849213,"about_ca_system_score_gemma":0.00001357523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006700108,"about_ca_topic_score_gemma":0.000001936421,"domain_scores_codex":[0.9982424,0.00005667032,0.0005202731,0.0003430592,0.0002965754,0.0005409716],"domain_scores_gemma":[0.9992495,0.0001406384,0.0000529982,0.0001677692,0.00004269835,0.000346448],"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":[0.0000654433,0.001163275,0.01933526,0.0006012283,0.001056582,0.0003870137,0.001500022,0.254726,0.3997051,0.0003404577,0.0001782325,0.3209414],"study_design_scores_gemma":[0.0002312506,0.0000888285,0.01094818,0.000137958,0.00003175161,0.00002907949,0.00002615541,0.983371,0.00456524,0.00002442761,0.0001910372,0.0003551075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7167109,0.00009048929,0.2810235,0.000008334246,0.0003072903,0.00008017954,0.000001978596,0.0008495111,0.0009278078],"genre_scores_gemma":[0.9928321,0.0000479379,0.006704374,0.00004697454,0.0002963182,0.000005637586,0.00001521519,0.00003763315,0.00001386017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.728645,"threshold_uncertainty_score":0.99999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02974547565582373,"score_gpt":0.2437646585279827,"score_spread":0.214019182872159,"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."}}