{"id":"W1965853050","doi":"10.1177/0164027512441612","title":"Structural Advantages of Good Health in Old Age","year":2012,"lang":"en","type":"article","venue":"Research on Aging","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Autonomy; Constraint (computer-aided design); Social network (sociolinguistics); Personal network; Test (biology); Position (finance); Leasehold estate; Health care; Psychology; Social network analysis; Gerontology; Demographic economics; Business; Economics; Medicine; Computer science; Sociology; Economic growth; Political science; Engineering; Social science; Social capital","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004859667,0.00004493898,0.000145983,0.0001895124,0.0003448466,0.00002660637,0.0001717248,0.00003408431,0.0001292985],"category_scores_gemma":[0.0003728544,0.0000395266,0.00002545233,0.0003724967,0.00014761,0.0001747909,0.0000497139,0.0003078479,0.00001530828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002815442,"about_ca_system_score_gemma":0.0002578423,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03272383,"about_ca_topic_score_gemma":0.006813639,"domain_scores_codex":[0.9974453,0.0006984267,0.0001753126,0.00009808417,0.0005721449,0.001010693],"domain_scores_gemma":[0.9989842,0.0005477867,0.00003456532,0.0001137369,0.00003398092,0.0002857316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001042046,0.00003951014,0.6445764,0.0002146744,0.000002899538,0.000004551463,0.02339528,0.000005331648,0.000009560586,0.3059891,0.001184309,0.02456795],"study_design_scores_gemma":[0.000217824,0.00004079537,0.9325517,0.0002056061,3.089585e-7,2.292002e-7,0.02146656,0.00001308425,0.00005140805,0.001166471,0.04421503,0.00007092969],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9478996,0.001080678,0.000001677096,0.02478543,0.0002084118,0.0002650629,0.000005836811,0.00001910387,0.02573425],"genre_scores_gemma":[0.9970722,0.0005684995,0.00008627863,0.0008481389,0.0001927555,0.000005013575,0.000001511155,0.000005691178,0.001219879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3048226,"threshold_uncertainty_score":0.9737173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2186675745035671,"score_gpt":0.5596085295051019,"score_spread":0.3409409550015348,"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."}}