{"id":"W2795718862","doi":"","title":"Intelligent In-House Monitoring for the Elderly","year":2007,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Heatstroke; Heat illness; Wearable computer; Vital signs; Medical emergency; Environmental science; Computer science; Real-time computing; Medicine; Meteorology; Embedded system","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":[0.0004257908,0.0001794142,0.000138797,0.0001318567,0.00009533759,0.00008719751,0.0002745444,0.00008485284,0.000002743372],"category_scores_gemma":[0.000119465,0.0001501205,0.00006557888,0.0003128466,0.00003352759,0.000230912,0.00004174904,0.0002235959,0.00002567168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001817812,"about_ca_system_score_gemma":0.000006688929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001411686,"about_ca_topic_score_gemma":0.000007758672,"domain_scores_codex":[0.9989002,9.076313e-7,0.0002661612,0.0001850331,0.0001612679,0.0004864363],"domain_scores_gemma":[0.9994903,0.0002190518,0.00002864025,0.00009448578,0.00009010221,0.00007744283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006435725,0.00004968525,0.2013559,0.0004773597,0.00009249761,0.00001237246,0.004054048,0.000809994,0.6439096,0.001757098,0.001026926,0.1463902],"study_design_scores_gemma":[0.0003195343,0.0001233333,0.01124079,0.0001830963,0.00001932965,0.000008422321,0.002807284,0.0003682436,0.9753445,0.0006906535,0.008557498,0.0003372646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810661,0.001171877,0.01309879,0.00003631793,0.001557646,0.0005206117,9.036704e-7,0.0005885459,0.001959184],"genre_scores_gemma":[0.996668,0.0001238433,0.001901756,0.000007483644,0.0010605,0.00009415147,1.840972e-7,0.00009482109,0.00004927175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.331435,"threshold_uncertainty_score":0.6121735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02189966070543329,"score_gpt":0.2572542746371261,"score_spread":0.2353546139316929,"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."}}