{"id":"W2981758614","doi":"10.29173/aar102","title":"Ageing, urban marginality, and health in Ghana","year":2019,"lang":"en","type":"article","venue":"Alberta Academic Review","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Slum; Neighbourhood (mathematics); Poverty; Population; Population ageing; Geography; Socioeconomics; Quality of life (healthcare); Health care; Gerontology; Economic growth; Environmental health; Psychology; Medicine; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0008375332,0.0001596474,0.0002219122,0.0006249412,0.001536351,0.0009760821,0.000245438,0.0002441962,0.002210979],"category_scores_gemma":[0.001559007,0.0001570728,0.00013341,0.001258051,0.001697047,0.001197058,0.001893245,0.0005107594,0.00008786212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001699554,"about_ca_system_score_gemma":0.001674548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03690046,"about_ca_topic_score_gemma":0.07403325,"domain_scores_codex":[0.999605,0.0002276111,0.00002630534,0.00002409672,0.00002677203,0.00009017732],"domain_scores_gemma":[0.999289,0.0001990398,0.0002380986,0.00001654122,0.00004642393,0.0002107834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001414851,0.0002677071,0.6230611,0.0006388821,0.00003452499,0.002878941,0.3235345,0.0001289613,0.0005109648,0.004095948,0.00239617,0.04231089],"study_design_scores_gemma":[0.00001733554,0.0001914738,0.5775877,0.000679312,0.0000237288,0.001142107,0.4057153,0.00008451744,0.00006896948,0.001356318,0.01311514,0.00001809007],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905292,0.004295274,0.00005631326,0.002290339,0.00002265375,0.00003209879,0.00008931512,0.00000173584,0.002683059],"genre_scores_gemma":[0.9971427,0.002249783,0.000086288,0.0002462709,0.00001221349,0.00002194052,0.00002500082,9.641833e-7,0.0002147459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03690046,"threshold_uncertainty_score":0.07337135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05446940383095982,"score_gpt":0.4054779712899904,"score_spread":0.3510085674590306,"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."}}