{"id":"W4408557973","doi":"10.2196/69052","title":"Detecting Older Adults’ Behavior Changes During Adverse External Events Using Ambient Sensing: Longitudinal Observational Study","year":2025,"lang":"en","type":"article","venue":"JMIR Nursing","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Nursing Research","keywords":"Observational study; Preprint; Adverse effect; Medicine; Environmental science; Internal medicine; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003402621,0.000273198,0.0003014109,0.000416554,0.0006046675,0.0001837586,0.0004064027,0.00008433867,0.000009988387],"category_scores_gemma":[0.00004553033,0.0003122209,0.000112523,0.000736136,0.00003667162,0.0007834992,0.0002300169,0.0002723681,0.00001074193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005965701,"about_ca_system_score_gemma":0.0001018061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001501842,"about_ca_topic_score_gemma":0.0001458268,"domain_scores_codex":[0.9975415,0.0002028127,0.0004309131,0.0007636481,0.000590412,0.0004706846],"domain_scores_gemma":[0.9987371,0.0001088022,0.0002737992,0.0004966095,0.0002807709,0.0001028955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001379047,0.00199414,0.6460285,0.0001448048,0.0001016784,0.0002610688,0.01303103,0.0001085272,0.03771529,0.00004098481,0.00001993015,0.3004161],"study_design_scores_gemma":[0.001514087,0.00007163623,0.9758027,0.00269002,0.00004835789,0.0001726556,0.002188387,0.01285273,0.004285821,0.00004277112,0.000007649433,0.0003232163],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.935805,0.00004729225,0.06073708,0.0001563904,0.001732603,0.001234145,0.000002370174,0.0002313923,0.00005375491],"genre_scores_gemma":[0.9959762,3.815161e-7,0.003530194,0.0000433349,0.0001985897,0.00006806358,0.000001587353,0.00002029612,0.0001613146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3297742,"threshold_uncertainty_score":0.999933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09365428110714744,"score_gpt":0.359197549335189,"score_spread":0.2655432682280416,"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."}}