{"id":"W4400910342","doi":"10.3390/vaccines12080826","title":"An Interrupted Time Series Analysis of the Impact of the COVID-19 Pandemic on Routine Vaccination Uptake in Kenya","year":2024,"lang":"en","type":"article","venue":"Vaccines","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Inro Consultants (Canada)","funders":"","keywords":"Interrupted Time Series Analysis; Pandemic; Coronavirus disease 2019 (COVID-19); Interrupted time series; Vaccination; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; Series (stratigraphy); Virology; Outbreak; Statistics; Mathematics; Biology; Psychological intervention; Nursing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001155937,0.0001875328,0.0005902282,0.0002503437,0.00006568756,0.0000154276,0.0004156137,0.00009168276,0.000389788],"category_scores_gemma":[0.007740673,0.00008202236,0.0004494687,0.002000692,0.00003096284,0.0000868904,0.0001696095,0.0001746514,0.000003539246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002734934,"about_ca_system_score_gemma":0.00007511229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007453977,"about_ca_topic_score_gemma":0.001818112,"domain_scores_codex":[0.9983632,0.0003953459,0.0006270285,0.0002646045,0.0001765244,0.000173286],"domain_scores_gemma":[0.9966981,0.002379284,0.000254959,0.0005508274,0.00007625414,0.00004060339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001487341,0.0001528191,0.9828162,0.0001491625,0.0008320806,0.00000108634,0.001702327,0.007644669,0.001375634,0.002026147,0.002202904,0.0009482232],"study_design_scores_gemma":[0.0002215478,0.0001459479,0.9656314,0.00006184845,0.0003818996,0.000001700219,0.0001212979,0.01716557,0.000153792,0.01584045,0.0001776786,0.00009690121],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964082,0.0001710097,0.0001833208,0.002574096,0.00006991152,0.0003028472,0.00006499041,0.0000841217,0.0001415367],"genre_scores_gemma":[0.9993917,0.00004522821,0.00006056547,0.0001955334,0.00003259322,0.00001570146,0.000006291634,0.00001250289,0.0002399204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01718485,"threshold_uncertainty_score":0.9266868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.165770240358327,"score_gpt":0.4505792080476327,"score_spread":0.2848089676893057,"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."}}