{"id":"W2532623572","doi":"10.1109/embc.2016.7592131","title":"Online learning of gait models for calculation of gait parameters","year":2016,"lang":"en","type":"article","venue":"","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Gait; Computer science; Gait cycle; Trajectory; Representation (politics); Wearable computer; Artificial intelligence; Gait analysis; SIGNAL (programming language); Key (lock); Physical medicine and rehabilitation; Kinematics","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":[0.0003450841,0.0008471293,0.0008053292,0.0007444155,0.0002011313,0.0005131378,0.0008522726,0.0005838213,0.001383245],"category_scores_gemma":[0.002128012,0.0004544909,0.0005457568,0.0005652129,0.0002294962,0.0006506513,0.0004607122,0.0007696534,0.001044717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002633277,"about_ca_system_score_gemma":0.0004585163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002897556,"about_ca_topic_score_gemma":0.004924723,"domain_scores_codex":[0.9997732,0.00003850368,0.00001658503,0.0000959674,0.00005605972,0.00001978332],"domain_scores_gemma":[0.9995672,0.0001833488,0.00006778997,0.00007563621,0.00008360652,0.00002236768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001554749,0.0003251218,0.00509763,0.0001432186,0.0001683885,0.0001407655,0.00007720776,0.3680086,0.01553353,0.00259645,0.003074232,0.6046795],"study_design_scores_gemma":[0.000005228477,0.00003643177,0.001000037,0.000009327766,0.000009869217,0.00004996263,0.000007906405,0.9953291,0.001519623,0.001532753,0.0004920195,0.000007708912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01809405,0.0001589682,0.9799804,0.00004903049,0.00003646602,0.0000315467,0.0001495717,0.0009680159,0.0005318835],"genre_scores_gemma":[0.6482996,0.0003479066,0.3472958,0.0001032183,0.00007578124,0.0001890478,0.001055398,0.0001991673,0.002434021],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002897556,"threshold_uncertainty_score":0.005761385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06197105811024578,"score_gpt":0.3784148780584654,"score_spread":0.3164438199482196,"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."}}