{"id":"W2883157124","doi":"10.3390/mti2030043","title":"Technology for Remote Health Monitoring in an Older Population: A Role for Mobile Devices","year":2018,"lang":"en","type":"article","venue":"Multimodal Technologies and Interaction","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sheridan College","funders":"Ontario Centres of Excellence","keywords":"Usability; Health care; Population ageing; Mobile technology; Mobile device; Population; Business; Internet privacy; Gerontology; Medicine; Computer science; Environmental health; Political science; World Wide Web; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003455042,0.000437695,0.0003739638,0.001614979,0.0009429667,0.003475255,0.000603575,0.001917175,0.004071232],"category_scores_gemma":[0.007161371,0.0002144802,0.0005124515,0.0009522756,0.001520059,0.005806148,0.002395146,0.001572572,0.0006007971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007246172,"about_ca_system_score_gemma":0.001280514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001412735,"about_ca_topic_score_gemma":0.002289474,"domain_scores_codex":[0.9981704,0.0009430772,0.0001007453,0.0001465796,0.000529929,0.0001091592],"domain_scores_gemma":[0.9933853,0.004710156,0.00043957,0.000191265,0.0009079335,0.0003658466],"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":[0.0000931988,0.0002441675,0.01930576,0.004120651,0.00005974099,0.001636321,0.01479509,0.0002453313,0.004561116,0.04179384,0.01762773,0.8955171],"study_design_scores_gemma":[0.0000525089,0.001308499,0.07792588,0.02651527,0.0002325949,0.02152172,0.03922826,0.00213588,0.003256951,0.03474229,0.7928587,0.0002214444],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1055066,0.6339183,0.03040857,0.1179307,0.001965355,0.0003439594,0.0001352765,0.0002723274,0.1095189],"genre_scores_gemma":[0.5064702,0.4236287,0.03480021,0.0168965,0.002459909,0.0003817792,0.00006906687,0.00006979203,0.01522393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004071232,"threshold_uncertainty_score":0.01827222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05916183947600782,"score_gpt":0.4771967971882379,"score_spread":0.4180349577122301,"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."}}