{"id":"W6920612562","doi":"10.60692/hq8z0-nq798","title":"Unmet need for COVID-19 vaccination coverage in Kenya","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vaccination; Population; Quarter (Canadian coin); Inequality; Intervention (counseling); Geospatial analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007614121,0.0002858799,0.0004113268,0.00061247,0.0006428905,0.0007417172,0.0004854926,0.0007274249,0.007093559],"category_scores_gemma":[0.003235013,0.0004245234,0.0004636494,0.0008663726,0.0003255178,0.001259974,0.0008184743,0.0009154258,0.0005301486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002398731,"about_ca_system_score_gemma":0.003200636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1412998,"about_ca_topic_score_gemma":0.1836831,"domain_scores_codex":[0.9993411,0.0002066287,0.00007142206,0.00007018339,0.00008523598,0.0002254882],"domain_scores_gemma":[0.9990564,0.0002265971,0.0003742217,0.00001675751,0.000127839,0.0001982917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003051504,0.0001797543,0.8985724,0.002514006,0.0002619923,0.002601605,0.003238396,0.001954853,0.002083414,0.003483786,0.01846789,0.06633669],"study_design_scores_gemma":[0.00006499892,0.0002459222,0.9592946,0.002813403,0.0001555046,0.001694992,0.00697211,0.005603851,0.0003313888,0.001433077,0.02131755,0.00007253976],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9357811,0.01379201,0.0008393595,0.02020589,0.0002532074,0.0002105844,0.01401833,0.00008214595,0.01481737],"genre_scores_gemma":[0.990339,0.004482429,0.001029355,0.0009934343,0.00004486477,0.0001035582,0.002081453,0.00001300472,0.0009128851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1412998,"threshold_uncertainty_score":0.2809547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2149991846941048,"score_gpt":0.3593059786711961,"score_spread":0.1443067939770913,"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."}}