{"id":"W4403715847","doi":"10.2196/54210","title":"Developing Independent Living Support for Older Adults Using Internet of Things and AI-Based Systems: Co-Design Study","year":2024,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Enterprise Ireland","keywords":"Independent living; Stakeholder; The Internet; Focus group; Aging in place; Population; Exploratory research; Psychology; Nursing; Perception; Gerontology; Needs assessment; Health care; Quality of life (healthcare); Telecare; Applied psychology; Medicine; Business; Telemedicine; Computer science; Marketing; Public relations; Sociology; World Wide Web; Environmental health","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02625122,0.0007972209,0.00099472,0.001862655,0.001896339,0.002117916,0.0009986968,0.001432189,0.002800341],"category_scores_gemma":[0.02147478,0.0006142164,0.001552783,0.0008417271,0.001172831,0.001574784,0.002092512,0.00112123,0.0005227004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002414015,"about_ca_system_score_gemma":0.00547735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001024078,"about_ca_topic_score_gemma":0.002597291,"domain_scores_codex":[0.9819681,0.01364407,0.001148097,0.0008739003,0.001234702,0.001131099],"domain_scores_gemma":[0.968648,0.01963239,0.002256416,0.001555684,0.005656599,0.002250854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.009990299,0.09304841,0.1739064,0.01629511,0.001158435,0.002947557,0.2566493,0.006656596,0.02658638,0.007827519,0.00340781,0.4015263],"study_design_scores_gemma":[0.01160327,0.2573553,0.1541127,0.006473747,0.002247753,0.002318813,0.4118869,0.01580772,0.02745342,0.005404584,0.1048572,0.0004785591],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9715703,0.00054562,0.01418569,0.0001915414,0.0000470846,0.01063013,0.00009351459,0.00003555834,0.002700425],"genre_scores_gemma":[0.9105091,0.001024533,0.058734,0.0004591635,0.00004450324,0.02608513,0.0001818967,0.00003182873,0.002929837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02625122,"threshold_uncertainty_score":0.1388314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03608178615557606,"score_gpt":0.3521440091493342,"score_spread":0.3160622229937582,"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."}}