{"id":"W4362475446","doi":"10.3138/jmvfh-2022-0064","title":"Employment and mental health among UK ex-service personnel during the initial period of the COVID-19 pandemic","year":2023,"lang":"en","type":"article","venue":"Journal of Military Veteran and Family Health","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Unemployment; Mental health; Coronavirus disease 2019 (COVID-19); Population; Military personnel; Service personnel; Psychology; Medicine; Demographic economics; Gerontology; Demography; Service (business); Psychiatry; Political science; Business; Economic growth; Environmental health; Economics; Sociology; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007968146,0.0001852793,0.000268091,0.001088791,0.0008984007,0.00112743,0.0003201838,0.0007267957,0.00237854],"category_scores_gemma":[0.002960145,0.0002287691,0.0003263782,0.0008893573,0.0005016066,0.0008104584,0.001269607,0.001051774,0.0003747493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170068,"about_ca_system_score_gemma":0.0006914114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0683895,"about_ca_topic_score_gemma":0.1169936,"domain_scores_codex":[0.9994684,0.0001188408,0.00005414595,0.00003266825,0.00007559218,0.0002504856],"domain_scores_gemma":[0.998772,0.0001210773,0.0005067525,0.00002649729,0.0002055485,0.0003681833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001581849,0.00007292251,0.9901199,0.0000508304,0.00002488362,0.0003035953,0.004358507,0.00003315464,0.0002278399,0.0000444453,0.0005229368,0.004082811],"study_design_scores_gemma":[0.0000012413,0.00006605883,0.9956663,0.00003527098,0.000002327756,0.00006113569,0.003886748,0.00001214795,0.00001294906,0.000005028777,0.000246969,0.00000389284],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979789,0.0006451446,0.00001128309,0.0003556087,0.00002355013,0.000008455574,0.0002467645,0.000001084512,0.0007292242],"genre_scores_gemma":[0.9988636,0.0004258508,0.0000112494,0.00008904373,0.00002309796,0.000007661673,0.0001382432,9.19062e-7,0.0004404832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0683895,"threshold_uncertainty_score":0.1359829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1171892591974712,"score_gpt":0.4147495352806903,"score_spread":0.2975602760832191,"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."}}