{"id":"W4378746240","doi":"10.3389/fnut.2023.1080181","title":"Derivation and validation of a nutrition-covered prognostic scoring system for extranodal NK/T-cell lymphoma","year":2023,"lang":"en","type":"article","venue":"Frontiers in Nutrition","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Key Technology Research and Development Program of Shandong; Shandong First Medical University; Natural Science Foundation of Shandong Province; China Postdoctoral Science Foundation","keywords":"Univariate; Multivariate analysis; Cohort; Lymphoma; Medicine; Multivariate statistics; Internal medicine; Proportional hazards model; Univariate analysis; Oncology; Malnutrition; T-cell lymphoma; International Prognostic Index; Cohort study; Clinical trial; Diffuse large B-cell lymphoma; Machine learning","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":[],"consensus_categories":[],"category_scores_codex":[0.0003485069,0.0001211938,0.0003252031,0.0006510119,0.00009695419,0.00001998113,0.00003961252,0.0001279533,0.000002258487],"category_scores_gemma":[0.00009265436,0.0001422233,0.00006305485,0.0005751508,0.00004152917,0.0001765331,0.00001105664,0.00006684686,0.000002515471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002275136,"about_ca_system_score_gemma":0.0000537438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001127472,"about_ca_topic_score_gemma":0.00000101589,"domain_scores_codex":[0.9987514,0.00004932017,0.000477287,0.0002642663,0.0002099789,0.0002477189],"domain_scores_gemma":[0.9993917,0.00009600531,0.000145862,0.0001219847,0.0001616017,0.00008288139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005916044,0.007676938,0.3226371,0.3939474,0.0001277839,0.00009180135,0.002107148,0.00005711597,0.1903429,0.004039948,0.04730921,0.02574657],"study_design_scores_gemma":[0.1472062,0.00264363,0.1062918,0.06366321,0.000529816,0.0002300924,0.01707877,0.0650382,0.5645459,0.02273264,0.008780967,0.001258808],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.97298,0.001809775,0.02049902,0.0006400297,0.0007587939,0.002924705,0.00006775081,0.0001813992,0.0001385215],"genre_scores_gemma":[0.9654002,0.001737701,0.03112242,0.00004543347,0.0002388536,0.0008139191,0.0005800753,0.00002709407,0.00003430653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3742029,"threshold_uncertainty_score":0.5799696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02429672053493545,"score_gpt":0.2782318608908576,"score_spread":0.2539351403559221,"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."}}