{"id":"W4389240153","doi":"10.1002/ctm2.1442","title":"Untargeted metabolomics identifies metabolic dysregulation of sphingolipids associated with aggressive chronic lymphocytic leukaemia and poor survival","year":2023,"lang":"en","type":"article","venue":"Clinical and Translational Medicine","topic":"Sphingolipid Metabolism and Signaling","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre hospitalier de l'Université Laval; Centre hospitalier universitaire de Québec","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Sphingolipid; Metabolomics; Lipidomics; Chronic lymphocytic leukemia; Cancer research; Sphingosine; Phenotype; Ceramide; Biology; Transcriptome; Pharmacology; Immunology; Leukemia; Apoptosis; Biochemistry; Bioinformatics; Gene; Gene expression; Receptor","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008988641,0.0001726327,0.0004854788,0.00009640207,0.00009280267,0.000009773256,0.0000829593,0.0001696497,0.00001684182],"category_scores_gemma":[0.0006276642,0.0001280039,0.00008226186,0.0002783125,0.0006246008,0.00001336536,0.00003196433,0.0001080224,0.000001095543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005116859,"about_ca_system_score_gemma":0.0002269962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000405486,"about_ca_topic_score_gemma":0.00005543954,"domain_scores_codex":[0.9985163,0.0001159191,0.0005602165,0.0003563265,0.0002578851,0.0001934055],"domain_scores_gemma":[0.9990326,0.0003033851,0.0002613474,0.0001325131,0.0001529463,0.0001172295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003123148,0.0002400362,0.4710386,0.0006113797,0.004682395,0.00004054524,0.001412691,0.004506465,0.4593243,0.01601973,0.00104288,0.03795793],"study_design_scores_gemma":[0.01016658,0.0004915908,0.9660352,0.0002773391,0.0007971652,0.00001629328,0.0001601041,0.006782377,0.01024731,0.002047582,0.00262698,0.0003514152],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988561,0.009941987,0.0004894494,0.0003968987,0.0003377477,0.0001552825,0.00004036985,0.00002219564,0.000055109],"genre_scores_gemma":[0.9952965,0.003030277,0.0001103871,0.0001049437,0.0007598071,0.000008267538,0.0005375209,0.00002000738,0.0001323014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4949967,"threshold_uncertainty_score":0.5219846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02803405910727255,"score_gpt":0.3073967633995851,"score_spread":0.2793627042923126,"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."}}