{"id":"W4407895265","doi":"10.3389/fpubh.2025.1526454","title":"Significance of the ARIMA epidemiological modeling to predict the rate of HIV and AIDS in the Kumba Health District of Cameroon","year":2025,"lang":"en","type":"article","venue":"Frontiers in Public Health","topic":"HIV/AIDS Impact and Responses","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); Response Biomedical (Canada); York University","funders":"","keywords":"Epidemiology; Human immunodeficiency virus (HIV); Autoregressive integrated moving average; Medicine; Environmental health; Virology; Computer science; Internal medicine; Time series","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":[0.003053041,0.0007618197,0.0004880716,0.001336482,0.0005218887,0.001635435,0.0006903266,0.0006605032,0.001466303],"category_scores_gemma":[0.009341361,0.0003678058,0.0007610788,0.00103434,0.0002558098,0.0007420661,0.0005857071,0.000997696,0.0001786339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001270406,"about_ca_system_score_gemma":0.002347695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09592894,"about_ca_topic_score_gemma":0.04413354,"domain_scores_codex":[0.998827,0.0007231621,0.00006276537,0.0002057194,0.0000624198,0.0001189757],"domain_scores_gemma":[0.9963614,0.002819399,0.0003013595,0.0000882091,0.0003206462,0.0001089899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003066693,0.0001903716,0.5112507,0.00009767122,0.0004049143,0.000598074,0.0003630205,0.4604471,0.0006549508,0.001877034,0.001459288,0.0223503],"study_design_scores_gemma":[0.0000124864,0.0000493384,0.02900559,0.00003685677,0.00006990405,0.00006122504,0.0002750038,0.9692113,0.0001283508,0.0005628695,0.000568377,0.00001874068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618031,0.0007160728,0.03237442,0.001451911,0.0001320187,0.0001261522,0.001450344,0.0001949398,0.001751098],"genre_scores_gemma":[0.9916346,0.0002219363,0.007148277,0.00003888425,0.00002468764,0.00005132359,0.0004707187,0.0000106317,0.000398914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09592894,"threshold_uncertainty_score":0.1907411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05938813173410913,"score_gpt":0.2911548515265546,"score_spread":0.2317667197924455,"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."}}