{"id":"W3114536287","doi":"10.1093/pubmed/fdaa217","title":"Associations of social cohesion and quality of life with objective and perceived built environments: a latent profile analysis among seniors","year":2020,"lang":"en","type":"article","venue":"Journal of Public Health","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute on Minority Health and Health Disparities; National Cancer Institute; National Institutes of Health; National Heart, Lung, and Blood Institute; Robert Wood Johnson Foundation; Silicon Valley Community Foundation; Stanford Prevention Research Center","keywords":"Cohesion (chemistry); Built environment; Quality of life (healthcare); Psychology; Structural equation modeling; Latent class model; Group cohesiveness; Gerontology; Social environment; Environmental health; Social psychology; Medicine; Computer science; Sociology; Engineering; Civil engineering","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":[0.002176651,0.0003054389,0.0003728692,0.001513871,0.0006263168,0.001142723,0.0003776822,0.0003332508,0.001392037],"category_scores_gemma":[0.004988914,0.0002410647,0.001033577,0.001542765,0.0004001514,0.0007227372,0.001458994,0.0005933724,0.0001557342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005776057,"about_ca_system_score_gemma":0.0006380797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009896475,"about_ca_topic_score_gemma":0.01372153,"domain_scores_codex":[0.9991016,0.0003569543,0.0001030134,0.0001293245,0.0001489389,0.0001600873],"domain_scores_gemma":[0.9980134,0.0004198808,0.0007289581,0.0002441361,0.0002586409,0.0003349402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003898443,0.00004977324,0.997933,0.000006713347,0.00006049225,0.000009279814,0.0003532111,0.00006455956,0.00004838503,0.00005166864,0.00005788263,0.001326002],"study_design_scores_gemma":[0.00000718867,0.00009702559,0.9965403,0.00001578428,0.00004351519,0.00003097273,0.001447973,0.001450628,0.00004878399,0.0001905048,0.0001205642,0.000006761095],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992994,0.00002489422,0.0003252057,0.00002675481,0.000001424578,0.0000105589,0.0002101812,0.000001930162,0.00009969994],"genre_scores_gemma":[0.9994234,0.00001772549,0.0001940304,0.000006289805,0.000001596799,0.00001933992,0.0002913966,0.000001203801,0.00004517466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009896475,"threshold_uncertainty_score":0.01967776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.103786543393684,"score_gpt":0.3739813294566491,"score_spread":0.270194786062965,"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."}}