{"id":"W2955420797","doi":"10.1111/ggi.13716","title":"Social determinants of the association among cerebrovascular disease, hearing loss and cognitive impairment in a middle‐aged or older population: Recurrent neural network analysis of the Korean Longitudinal Study of Aging (2014–2016)","year":2019,"lang":"en","type":"article","venue":"Geriatrics and gerontology international/Geriatrics & gerontology international","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Medicine; Association (psychology); Hearing loss; Cognition; Socioeconomic status; Population; Disease; Longitudinal study; Gerontology; Audiology; Psychiatry; Psychology; Internal medicine; Pathology; Environmental health","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003934828,0.0007389649,0.0006930134,0.0009590852,0.0003386359,0.0006715917,0.0007832596,0.0004576787,0.001375137],"category_scores_gemma":[0.006262699,0.0003191415,0.00225203,0.0009425117,0.0002836047,0.0006863314,0.0009238908,0.001181979,0.0002398583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007231286,"about_ca_system_score_gemma":0.0008675614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02532424,"about_ca_topic_score_gemma":0.02623487,"domain_scores_codex":[0.9989631,0.0004175446,0.0001023542,0.0003034299,0.00007598086,0.0001374776],"domain_scores_gemma":[0.9978122,0.0007081112,0.0005072572,0.0003097346,0.0004021832,0.0002604797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003314617,0.0001316775,0.9865496,0.00004810663,0.0009290933,0.00009328079,0.0001195235,0.003994042,0.0002533667,0.000139761,0.0006304812,0.00677966],"study_design_scores_gemma":[0.00003911952,0.0002357938,0.8991638,0.00005407723,0.0009489233,0.0001373212,0.000345955,0.09754609,0.0002727377,0.0007103259,0.0005121646,0.00003370819],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961188,0.000345122,0.001623918,0.0002787483,0.00003948706,0.0000183218,0.001344801,0.00002226434,0.000208471],"genre_scores_gemma":[0.997154,0.0001165382,0.0006606633,0.00004196467,0.00001488633,0.00002101388,0.001773102,0.000004338338,0.0002134797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02532424,"threshold_uncertainty_score":0.05035371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03958277663488518,"score_gpt":0.3469617808538605,"score_spread":0.3073790042189753,"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."}}