{"id":"W6939707191","doi":"10.6084/m9.figshare.28558040.v1","title":"Additional file 1 of Corruption risks in COVID-19 vaccine deployment: lessons learned for future pandemic preparedness","year":2025,"lang":"en","type":"article","venue":"Open MIND","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pandemic; Preparedness; Government (linguistics); Language change; Coronavirus disease 2019 (COVID-19)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003426295,0.0006360954,0.000894862,0.002034548,0.0007695265,0.001874532,0.001760721,0.001688719,0.848228],"category_scores_gemma":[0.06307042,0.0004667735,0.0009410779,0.004050004,0.0002772083,0.0027135,0.001260543,0.001437002,0.1426685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001973162,"about_ca_system_score_gemma":0.00406003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02949682,"about_ca_topic_score_gemma":0.04494045,"domain_scores_codex":[0.9986154,0.0004334082,0.0002228663,0.0002162452,0.0003342603,0.0001778597],"domain_scores_gemma":[0.9533898,0.03649704,0.002317072,0.001534887,0.005325566,0.0009356283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.00009527429,0.00004976138,0.001977152,0.00112752,0.00002783189,0.00003676424,0.00005112409,0.0003614901,0.00001207313,0.001088004,0.9874136,0.007759453],"study_design_scores_gemma":[0.002821054,0.0002982631,0.05528363,0.01086081,0.0003102483,0.000497997,0.002989525,0.006916898,0.0003510214,0.04471296,0.8747146,0.0002430281],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0002550961,0.00006156047,0.0003757982,0.0008683185,0.00007607054,0.00008073794,0.9956144,0.0001367997,0.002531206],"genre_scores_gemma":[0.03593673,0.0006657269,0.01108679,0.003614422,0.000327034,0.002757682,0.9163814,0.0008008227,0.02842955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.848228,"threshold_uncertainty_score":0.2164843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09862702434277881,"score_gpt":0.3668264561013425,"score_spread":0.2681994317585636,"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."}}