{"id":"W7132990447","doi":"","title":"Assessing Frailty Using Sensors and Machine Learning in Home Settings","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Frailty in Older Adults","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute","funders":"","keywords":"Classifier (UML); Gradient boosting; Frailty Index; Scale (ratio); Identification (biology); Receiver operating characteristic; Activities of daily living; Focus group","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":[0.006012894,0.0005502053,0.0009866483,0.003143593,0.0002347839,0.001432525,0.0006652292,0.0007576412,0.0006658559],"category_scores_gemma":[0.01940123,0.0002891738,0.001456152,0.002194418,0.0004292815,0.001292147,0.0007109484,0.0005630914,0.000178496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007957523,"about_ca_system_score_gemma":0.001021295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003845321,"about_ca_topic_score_gemma":0.005822308,"domain_scores_codex":[0.9958592,0.002121542,0.0005511945,0.0004871184,0.0009019272,0.00007902951],"domain_scores_gemma":[0.9873595,0.009514477,0.001163722,0.0002704558,0.001615828,0.00007602259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003959785,0.0001486352,0.0597658,0.0301348,0.001439716,0.0002459622,0.00148064,0.00582457,0.003435533,0.002122058,0.004098294,0.8909081],"study_design_scores_gemma":[0.0004045505,0.0077232,0.4996772,0.1123194,0.01432187,0.004704979,0.009527792,0.09368515,0.0412117,0.02755044,0.1880559,0.0008178675],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2187298,0.637189,0.1188729,0.003447314,0.0005597218,0.00121143,0.004137577,0.0007041633,0.0151481],"genre_scores_gemma":[0.7102717,0.184461,0.09920321,0.001648869,0.0002892922,0.001262887,0.001484488,0.00004192097,0.001336606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006012894,"threshold_uncertainty_score":0.03179955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04733206042443276,"score_gpt":0.3803016552245303,"score_spread":0.3329695948000975,"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."}}