{"id":"W3198532616","doi":"10.3390/app11177986","title":"An Exergame Solution for Personalized Multicomponent Training in Older Adults","year":2021,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Active and Assisted Living programme; European Commission","keywords":"Personalization; Psychological intervention; Wearable computer; Urinary incontinence; Balance (ability); Applied psychology; Cognition; Rehabilitation; Physical medicine and rehabilitation; Session (web analytics); Psychology; Human–computer interaction; Physical therapy; Computer science; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.001085042,0.00009103656,0.0001787635,0.00006724769,0.0006485255,0.00001662693,0.000152798,0.0001003856,0.00003884468],"category_scores_gemma":[0.00003847112,0.00008142043,0.00004107825,0.0002656362,0.0001247849,0.0001339048,0.00002948136,0.0001613614,0.00002509328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005593299,"about_ca_system_score_gemma":0.000283518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009314587,"about_ca_topic_score_gemma":0.0007678533,"domain_scores_codex":[0.9985287,0.0001348632,0.000292485,0.0003931917,0.0002063801,0.0004443407],"domain_scores_gemma":[0.9994527,0.0001865128,0.0001095446,0.0001225672,0.00005390217,0.00007480045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004039534,0.001471166,0.0108277,0.0005279702,0.00001926262,0.000006324213,0.1514076,0.00002011153,0.607577,0.09411017,0.0008404095,0.1327883],"study_design_scores_gemma":[0.01435148,0.0001883916,0.679168,0.001083063,0.00003378214,0.000003522751,0.2097616,0.07509849,0.0004718685,0.01276983,0.006330649,0.0007393375],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879266,0.0001496109,0.00607965,0.0005070561,0.0004629411,0.0008256928,0.000009413175,0.00006039567,0.003978633],"genre_scores_gemma":[0.9917312,0.0000219549,0.006903289,0.0004460215,0.0001496397,0.0003975252,0.00004472662,0.000007537052,0.0002981492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6683403,"threshold_uncertainty_score":0.4987999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05991046294731781,"score_gpt":0.384653526536874,"score_spread":0.3247430635895562,"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."}}