{"id":"W4403816026","doi":"10.1093/eurpub/ckae144.1633","title":"Telemonitoring activities of daily living in home healthcare services to support aging in place","year":2024,"lang":"en","type":"article","venue":"European Journal of Public Health","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; McGill University Health Centre; Université de Sherbrooke; Université de Montréal; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal","funders":"","keywords":"Aging in place; Health care; Activities of daily living; Gerontology; Medicine; Physical therapy; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009580554,0.0001329652,0.0001311626,0.0003906456,0.0008970171,0.0007523682,0.0004938288,0.0002247461,0.002153378],"category_scores_gemma":[0.001767838,0.00007103728,0.0001362916,0.000437754,0.0003450097,0.0003165353,0.0008009066,0.0002357185,0.0001656068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002042766,"about_ca_system_score_gemma":0.003626986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09872021,"about_ca_topic_score_gemma":0.2407724,"domain_scores_codex":[0.9994282,0.0003291572,0.00002119247,0.00003984157,0.00009073482,0.00009077974],"domain_scores_gemma":[0.9991364,0.0002668284,0.0001194488,0.00004250737,0.0001826028,0.0002522301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000264309,0.001295177,0.3179768,0.001196144,0.00006321886,0.001130937,0.04527549,0.001154121,0.009516141,0.0007935243,0.01065378,0.6106802],"study_design_scores_gemma":[0.00008731778,0.001400318,0.8732787,0.001092774,0.0000896833,0.0006717914,0.07321812,0.003441258,0.002083817,0.0004948901,0.0440974,0.00004397272],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985064,0.0007651208,0.002450169,0.00111715,0.00002854869,0.0003500984,0.0003205241,0.00006584827,0.009838504],"genre_scores_gemma":[0.9960886,0.0004372198,0.002201534,0.0002282697,0.0000155174,0.00008663085,0.00005799603,0.000003066571,0.0008810836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09872021,"threshold_uncertainty_score":0.1962911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0652566003913092,"score_gpt":0.3198344052302795,"score_spread":0.2545778048389703,"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."}}