{"id":"W4385564977","doi":"10.1093/abm/kaad042","title":"Who Benefits From Helping? Moderators of the Association Between Informal Helping and Mortality","year":2023,"lang":"en","type":"article","venue":"Annals of Behavioral Medicine","topic":"Nonprofit Sector and Volunteering","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute on Aging; Canadian Institutes of Health Research; University of Michigan; National Institutes of Health; Michael Smith Health Research BC; U.S. Social Security Administration","keywords":"Poisson regression; Ethnic group; Demography; Psychology; Association (psychology); Gerontology; Health psychology; Medicine; Public health; Population; Sociology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004549896,0.0004479845,0.0006400858,0.0005130045,0.0008114684,0.0008392824,0.0006361573,0.0006343932,0.004501947],"category_scores_gemma":[0.02000351,0.0002475313,0.001209877,0.0004629135,0.0007940601,0.0006284351,0.002133669,0.00111879,0.0002241848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004391152,"about_ca_system_score_gemma":0.001013429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006166426,"about_ca_topic_score_gemma":0.009372601,"domain_scores_codex":[0.9971414,0.001625175,0.0001433186,0.0003883666,0.0002093476,0.0004922781],"domain_scores_gemma":[0.9900359,0.005342992,0.002129327,0.0007987785,0.0004516526,0.001241357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006052461,0.0001856167,0.9855924,0.0001286409,0.0008358086,0.00007734157,0.001402919,0.0002167653,0.0002925914,0.0005491229,0.000509828,0.009603869],"study_design_scores_gemma":[0.00002516548,0.0002190032,0.9957319,0.0001156061,0.0004726995,0.0000589297,0.000871595,0.000427148,0.0001186313,0.0009751715,0.0009713168,0.00001282555],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933727,0.001591799,0.000949136,0.001734869,0.00008084121,0.00004719822,0.0005001623,0.00001959317,0.001703731],"genre_scores_gemma":[0.998782,0.0002260638,0.0003478507,0.0001193476,0.00003905084,0.00003867222,0.00009823354,0.000005999581,0.0003428341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006166426,"threshold_uncertainty_score":0.0240624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1570191846568466,"score_gpt":0.4080242186305921,"score_spread":0.2510050339737456,"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."}}