{"id":"W4405854798","doi":"10.1093/milmed/usae573","title":"Correction To: The Canadian Longitudinal Study on Aging: A Vehicle for Research on Aging in Older Veterans","year":2024,"lang":"en","type":"erratum","venue":"Military Medicine","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Gerontology; Longitudinal study; Medicine; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00813336,0.00025597,0.0003710868,0.0006874832,0.001199131,0.00004827043,0.0005500153,0.0001654696,0.0001955855],"category_scores_gemma":[0.001342072,0.0001796698,0.00009030705,0.001001409,0.0004055479,0.00004621595,0.00005413183,0.001566616,0.00008508023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002773499,"about_ca_system_score_gemma":0.0009836112,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9027887,"about_ca_topic_score_gemma":0.9935398,"domain_scores_codex":[0.9953997,0.0008719828,0.000395627,0.0008148162,0.001618436,0.0008994042],"domain_scores_gemma":[0.9980576,0.0008316367,0.00002589425,0.0005308789,0.0001895963,0.0003643825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004842918,0.0001803268,0.01133192,0.00009848244,0.00003540125,0.00003798469,0.100305,0.00002639711,5.036397e-7,0.00007088083,0.8852541,0.002610503],"study_design_scores_gemma":[0.0006363392,0.002709321,0.1947961,0.002659379,0.0000680081,5.886648e-7,0.1064579,0.0001759651,6.343956e-7,0.000388829,0.6918489,0.0002580044],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2518154,0.0068638,0.00001110899,0.3252867,0.2054093,0.01516288,0.0001064336,0.0001813027,0.195163],"genre_scores_gemma":[0.8861527,0.0001537893,0.000001754711,0.001015922,0.00650822,0.0005674066,0.00007577515,0.00003978758,0.1054846],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6343373,"threshold_uncertainty_score":0.9222864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4441573693114654,"score_gpt":0.5321028086694403,"score_spread":0.08794543935797483,"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."}}