{"id":"W4391916886","doi":"10.1101/2024.02.16.24302584","title":"Quantifying the impact of cascade inequalities: a modelling study on the prevention impacts of antiretroviral therapy scale-up in Eswatini","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"HIV/AIDS Research and Interventions","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of Toronto","funders":"National Institute of Allergy and Infectious Diseases; Johns Hopkins University; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Ministry of Colleges and Universities; University of Cape Town","keywords":"Antiretroviral therapy; Cascade; Scale (ratio); Human immunodeficiency virus (HIV); Inequality; Environmental science; Medicine; Mathematics; Virology; Engineering; Geography; Viral load; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002565178,0.0009196501,0.0008055381,0.0007454082,0.0007655578,0.001752737,0.002009166,0.00201336,0.004037636],"category_scores_gemma":[0.005033529,0.0004792424,0.001720478,0.001015375,0.0008227881,0.001757743,0.001803301,0.001894184,0.0002274425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004425616,"about_ca_system_score_gemma":0.00211099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06001095,"about_ca_topic_score_gemma":0.03711254,"domain_scores_codex":[0.9991529,0.000399692,0.00002505024,0.0001451172,0.00004296749,0.0002342906],"domain_scores_gemma":[0.9962148,0.002696235,0.0004022945,0.0001938765,0.000263194,0.0002295441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000393798,0.0004177013,0.02567069,0.00009463553,0.0001786956,0.0003601401,0.0002865291,0.9566547,0.0005811832,0.01070103,0.0007564697,0.003904477],"study_design_scores_gemma":[0.00005400652,0.0001924504,0.007715815,0.00002283515,0.0000803428,0.00003098312,0.0002648367,0.9879264,0.0002275512,0.002761542,0.0006978334,0.00002548602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836025,0.0002373663,0.008574135,0.000594498,0.00002193395,0.0001587359,0.001020038,0.00004875295,0.005742061],"genre_scores_gemma":[0.9946305,0.0001562937,0.002760166,0.00007249379,0.000009864661,0.0001583746,0.0004742745,0.00001088122,0.00172718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06001095,"threshold_uncertainty_score":0.1193233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1757041686581738,"score_gpt":0.4456092611717553,"score_spread":0.2699050925135815,"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."}}