{"id":"W2134357447","doi":"10.1186/1743-0003-9-28","title":"Dynamic stability requirements during gait and standing exergames on the wii fit® system in the elderly","year":2012,"lang":"en","type":"article","venue":"Journal of NeuroEngineering and Rehabilitation","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut de Readaptation Gingras Lindsay de Montreal; Université de Montréal; Centre for Interdisciplinary Research in Rehabilitation","funders":"Université de Montréal; Centre for Interdisciplinary Research in Rehabilitation","keywords":"Balance (ability); Physical medicine and rehabilitation; Gait; Kinematics; Rehabilitation; Dynamic balance; Stability (learning theory); Force platform; Task (project management); Simulation; Psychology; Computer science; Physical therapy; Medicine; Engineering; Machine learning","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":[0.001899458,0.00009276868,0.0001557472,0.00009904504,0.0002444401,0.00001543215,0.00007045334,0.00004546448,0.000001003582],"category_scores_gemma":[0.0003631127,0.00005265002,0.00004095196,0.0001132808,0.00003294575,0.0002484752,0.00001845919,0.0004451578,7.387108e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001288908,"about_ca_system_score_gemma":0.0000136686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005323836,"about_ca_topic_score_gemma":0.000003756913,"domain_scores_codex":[0.998546,0.0004817467,0.000462486,0.00008765737,0.0002065764,0.0002155201],"domain_scores_gemma":[0.9983634,0.001191757,0.0002182181,0.0001242195,0.00005262932,0.00004982403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009279124,0.001008188,0.7404169,0.009789358,0.0001086604,0.00002108183,0.09569731,0.0005522413,0.1372341,0.007339661,0.0004117596,0.006492866],"study_design_scores_gemma":[0.0005471866,0.0003537155,0.9833384,0.0008632519,0.00001561738,0.00001533667,0.01366766,0.0009533928,0.000003488123,0.00007962775,0.0001088131,0.00005351314],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975163,0.0003691141,0.0001209089,0.001100468,0.0004770725,0.0003299832,0.000001767895,0.00001341444,0.0000709296],"genre_scores_gemma":[0.9995762,0.0001252556,0.0001424493,0.0000274674,0.0000882683,0.00001606802,3.386127e-7,0.000009817462,0.00001417327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2429215,"threshold_uncertainty_score":0.2147005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0265245903307952,"score_gpt":0.3182588430249872,"score_spread":0.291734252694192,"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."}}