{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001075324,0.0000825451,0.0002820195,0.000069807,0.0001887742,0.00001045635,0.0001603966,0.0001051613,0.00002616963],"category_scores_gemma":[0.0002017783,0.00006300665,0.00005513865,0.0004108258,0.0001737932,0.0002036132,0.00007391333,0.0001158914,0.000001164019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001961943,"about_ca_system_score_gemma":0.00004669106,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02980815,"about_ca_topic_score_gemma":0.002995158,"domain_scores_codex":[0.998638,0.00007618018,0.0003339576,0.0001144834,0.000604353,0.0002329702],"domain_scores_gemma":[0.9992263,0.0001365863,0.0002561273,0.0001291754,0.0001719216,0.00007990982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000334127,0.000006888091,0.9844784,0.00001272942,0.00002214507,2.593152e-7,0.0106362,0.000005361233,0.0006273341,0.0002796849,0.0002162793,0.003711346],"study_design_scores_gemma":[0.0001682832,0.00005859309,0.9928933,0.0002148793,0.00006053721,1.829044e-8,0.002660317,0.0000250657,0.003346598,0.0002742287,0.000234306,0.00006386344],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997887,0.0001673932,0.00000496951,0.001029294,0.0002518452,0.0001458108,0.00006012603,0.00003339305,0.0004201397],"genre_scores_gemma":[0.9993328,0.000152318,0.000006847213,0.0000847883,0.000304811,0.000003806009,0.00001288356,0.000006477248,0.00009525636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02681299,"threshold_uncertainty_score":0.9766524,"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."}}