{"id":"W2725991551","doi":"10.1093/geroni/igx004.2634","title":"THE INDIVIDUAL AND STRUCTURAL DETERMINANTS OF AGING WELL IN CANADA AND MEXICO","year":2017,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Socioeconomic status; Gerontology; Index (typography); Healthy aging; Presentation (obstetrics); Social determinants of health; Psychology; Demography; Medicine; Environmental health; Public health; Sociology; Population","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":[0.0001457319,0.00005824869,0.00007704655,0.0001200348,0.00006140381,0.00004265511,0.0001106513,0.00002272049,4.54508e-7],"category_scores_gemma":[0.00007159851,0.00005001255,0.000002240751,0.0001211885,0.00003645318,0.00009599336,0.00005319732,0.0001201118,3.656587e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004143625,"about_ca_system_score_gemma":0.00002000207,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04929369,"about_ca_topic_score_gemma":0.2906218,"domain_scores_codex":[0.9995791,0.00000288828,0.000184474,0.00006032344,0.00006095887,0.0001123007],"domain_scores_gemma":[0.9997771,0.00004099126,0.00004402145,0.0001204294,0.00001200722,0.000005461331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[4.362246e-7,2.620299e-7,0.9151327,0.00003134323,0.000003138365,0.00000404634,0.0001586801,0.001631612,0.0001821473,0.0003026181,0.000009872975,0.08254315],"study_design_scores_gemma":[0.000138033,0.000001996087,0.9616289,0.00007737206,9.389198e-7,0.000003757605,0.0002333504,0.02832905,0.008906547,0.0005196062,0.00009114825,0.0000693443],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993322,0.0002236979,0.00003753649,0.00008220284,0.0001575519,0.00003338563,0.000001820327,0.00002521662,0.000106359],"genre_scores_gemma":[0.9997495,0.00003444514,0.00019198,0.000004429896,0.000007577379,0.000002718663,5.883518e-7,0.000006106926,0.000002646061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2413281,"threshold_uncertainty_score":0.9570372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01300348650391948,"score_gpt":0.2296771322925275,"score_spread":0.216673645788608,"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."}}