{"id":"W4327581317","doi":"10.1097/js9.0000000000000060","title":"COVID-19 vaccine wastage and distribution disparities in Pakistan: an editorial","year":2023,"lang":"en","type":"editorial","venue":"International Journal of Surgery","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vaccination; Medicine; Global health; Preparedness; Population; Equity (law); Pandemic; Environmental health; Public health; Multinational corporation; Economic growth; Coronavirus disease 2019 (COVID-19); Business; Infectious disease (medical specialty); Disease; Virology; Political science; Finance","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003618368,0.0001895844,0.0005182705,0.0003789482,0.0001605557,0.0003637345,0.0004813513,0.0005196608,0.0001286336],"category_scores_gemma":[0.01419596,0.0001881871,0.0001900307,0.0002131808,0.00003360995,0.000845262,0.00008239317,0.0007745728,0.000005716324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001050596,"about_ca_system_score_gemma":0.003303855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004385138,"about_ca_topic_score_gemma":0.005133817,"domain_scores_codex":[0.9961995,0.0003010075,0.0009179247,0.00022528,0.002059094,0.0002971923],"domain_scores_gemma":[0.9923918,0.005257153,0.000757288,0.0001009852,0.001091246,0.000401502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003862263,0.00006849981,0.01364377,0.0000334231,0.00007210497,0.0005456888,0.0006215105,0.00000885812,0.000001975462,0.0003690014,0.9835489,0.0007000591],"study_design_scores_gemma":[0.0005858446,0.00003291448,0.002852977,0.0002035282,0.00002450639,0.000004109103,0.000693511,0.000001892886,0.000001102569,0.001945667,0.9934675,0.000186508],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0097859,0.0004812105,0.00007811687,0.00355775,0.9853852,0.00006428194,0.0005776129,0.00002837394,0.00004155799],"genre_scores_gemma":[0.01991637,0.007996685,0.000006940243,0.00006142811,0.9711443,0.000004418141,0.0005253658,0.00002433683,0.0003202022],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01424094,"threshold_uncertainty_score":0.9941079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03107980975134045,"score_gpt":0.3791098634572549,"score_spread":0.3480300537059145,"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."}}