{"id":"W4321605570","doi":"10.1101/2023.02.17.23286087","title":"Analysis of sex disparities in under-five mortality rates in Ghana: Insights from vector autoregressive modeling","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Variance decomposition of forecast errors; Granger causality; Autoregressive model; Vector autoregression; Demography; Distributed lag; Child mortality; Econometrics; Statistics; Economics; Mathematics; Population; Sociology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00179332,0.000228085,0.0002960773,0.0007749526,0.0001379388,0.0007287373,0.0002672187,0.0002326551,0.002193299],"category_scores_gemma":[0.005363291,0.0001333572,0.000496505,0.001038048,0.0002031035,0.0004934413,0.0003995457,0.000526074,0.0001723427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004873461,"about_ca_system_score_gemma":0.000822623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0282463,"about_ca_topic_score_gemma":0.01739856,"domain_scores_codex":[0.9994801,0.0003322123,0.00002379158,0.00006197099,0.00004946128,0.00005255629],"domain_scores_gemma":[0.9972812,0.001859302,0.0005301818,0.0001083784,0.0001701134,0.00005076746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001480707,0.00008717773,0.8676171,0.0001439172,0.0003261868,0.0004924046,0.001407907,0.04701581,0.000854167,0.01402188,0.003178139,0.06470728],"study_design_scores_gemma":[0.00001539654,0.0001370419,0.492711,0.0002401471,0.0002093581,0.0001545973,0.003316487,0.4794539,0.0005066759,0.01566132,0.007558558,0.00003547936],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9697417,0.001580759,0.02140154,0.002519449,0.00006243198,0.00003546712,0.001302525,0.00007251518,0.003283733],"genre_scores_gemma":[0.9962667,0.0005268044,0.002201042,0.00003642285,0.0000169007,0.00001137949,0.0003543069,0.00001039464,0.0005761221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0282463,"threshold_uncertainty_score":0.05616379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1471877429177472,"score_gpt":0.4577194967245214,"score_spread":0.3105317538067742,"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."}}