{"id":"W2100733319","doi":"10.3934/publichealth.2015.1.115","title":"Predictors of Residential Mobility among Older Canadians and Impact on Analyses of Place and Health Relationships","year":2015,"lang":"en","type":"article","venue":"AIMS Public Health","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de Santé Publique du Québec; Université du Québec à Montréal","funders":"","keywords":"Neighbourhood (mathematics); Socioeconomic status; Population health; Cross-sectional study; Social determinants of health; Population; Gerontology; Demography; Psychology; Environmental health; Geography; Public health; Medicine; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006830368,0.0001016,0.0003956805,0.000195278,0.0004486528,0.00004240792,0.0001070445,0.0001002971,0.00002729377],"category_scores_gemma":[0.001213066,0.00008651146,0.00004215381,0.0004021002,0.0003887207,0.0002913729,0.00002557945,0.0001988399,4.74044e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005718151,"about_ca_system_score_gemma":0.008100197,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8479178,"about_ca_topic_score_gemma":0.5798252,"domain_scores_codex":[0.9972126,0.0009947473,0.0005504596,0.0002154461,0.0004371295,0.0005896225],"domain_scores_gemma":[0.9972077,0.0004199921,0.0003357379,0.0001991142,0.0001465891,0.001690886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006994303,0.00004395343,0.9645215,0.0001601685,0.00001787909,2.506229e-7,0.02069618,0.0000149613,3.642639e-8,0.003465475,0.01033651,0.0007361439],"study_design_scores_gemma":[0.0002838957,0.0001988774,0.9835851,0.00005536159,0.000003881186,4.010098e-7,0.01413691,0.00004862699,5.055045e-7,0.0001864212,0.001442204,0.00005778931],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9488535,0.0008344686,0.00002888733,0.04872476,0.0001511583,0.0004278563,0.00007950062,0.00002203053,0.0008778559],"genre_scores_gemma":[0.9982168,0.0003769,0.00005706397,0.001113297,0.00007836664,0.000006265172,0.00001077117,0.00000761144,0.0001329065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2680926,"threshold_uncertainty_score":0.997523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1751986231965585,"score_gpt":0.4375201484787661,"score_spread":0.2623215252822076,"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."}}