{"id":"W4389344116","doi":"10.1016/j.clnesp.2023.09.420","title":"The use of preoperative nutrition score to predict malnutrition in children","year":2023,"lang":"en","type":"article","venue":"Clinical Nutrition ESPEN","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Pediatric Oncology Group","funders":"","keywords":"Medicine; Malnutrition; Standard score; Intensive care medicine; Pediatrics; Internal medicine; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0009037494,0.0005040983,0.0004214072,0.0009798668,0.0001944344,0.0007233218,0.0002535281,0.0005448922,0.0009057999],"category_scores_gemma":[0.006315783,0.0001870042,0.0005077624,0.0006244465,0.0003689357,0.000611282,0.0004380139,0.0008050274,0.0002211411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003131289,"about_ca_system_score_gemma":0.0006498276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002691688,"about_ca_topic_score_gemma":0.003546948,"domain_scores_codex":[0.9994356,0.0002123529,0.00007735672,0.00006003636,0.0001324574,0.00008213365],"domain_scores_gemma":[0.9974438,0.001119137,0.0006505508,0.00008762239,0.0003458633,0.0003530477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001546127,0.00003245423,0.9958111,0.00001280004,0.00002918457,0.00004343788,0.0000298894,0.0001151013,0.0001143994,0.00001792088,0.0001275926,0.003511444],"study_design_scores_gemma":[0.00001245856,0.0004547616,0.9954934,0.00004666352,0.00007267808,0.0005046962,0.0002810783,0.00219754,0.0004779767,0.00006822313,0.0003777077,0.00001268874],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969675,0.0009352231,0.000322077,0.0002332256,0.00005166401,0.000006855916,0.0002177361,0.00001424255,0.00125142],"genre_scores_gemma":[0.9989406,0.0002264806,0.0003624895,0.00002724549,0.00001871227,0.000005587105,0.0002336248,0.000003598341,0.0001815707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002691688,"threshold_uncertainty_score":0.00535202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2127489108080135,"score_gpt":0.4433810528052963,"score_spread":0.2306321419972828,"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."}}