{"id":"W4220916551","doi":"10.1159/000522242","title":"Tackling Protein-Calorie Malnutrition during World Crises","year":2022,"lang":"en","type":"review","venue":"Annals of Nutrition and Metabolism","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Malnutrition; Environmental health; Food security; Business; Psychological intervention; Population; Pandemic; Economic growth; Productivity; Medicine; Development economics; Economics; Agriculture; Geography; Disease; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000369728,0.000565775,0.001972719,0.001319717,0.0004179744,0.0001482691,0.0003214722,0.000232888,0.0005646792],"category_scores_gemma":[0.0001013497,0.0005617513,0.0008017001,0.0009700407,0.0001231282,0.0004427355,0.0001676634,0.0006881019,0.00001369936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003314397,"about_ca_system_score_gemma":0.00002768333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000030563,"about_ca_topic_score_gemma":0.000003799378,"domain_scores_codex":[0.9967033,0.0004542835,0.001165436,0.0006798041,0.0005012023,0.0004960339],"domain_scores_gemma":[0.9983861,0.0001594171,0.0006691461,0.0004027392,0.0001621195,0.0002204136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005637118,0.003791896,0.000007940135,0.1880939,0.000408803,0.00007245514,0.0002675299,3.46012e-7,0.0001365588,0.002345669,0.01871411,0.7855971],"study_design_scores_gemma":[0.001472342,0.00004951443,0.00004927308,0.0124005,0.0004930102,0.00004894235,0.00004252389,5.468367e-7,0.001472562,0.001992139,0.9814247,0.0005538823],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0009962161,0.9936585,0.000002884204,0.001308613,0.0009349555,0.001967908,0.0004811385,0.000146281,0.0005035029],"genre_scores_gemma":[0.0004324129,0.9957613,0.0002876304,0.0003655686,0.001304785,0.0007893475,0.0006298365,0.0001031476,0.0003259574],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9627107,"threshold_uncertainty_score":0.9996834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1138606453534394,"score_gpt":0.3709161619719019,"score_spread":0.2570555166184625,"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."}}