{"id":"W4401702221","doi":"10.1038/s41588-024-01853-0","title":"Comprehensive molecular profiling of multiple myeloma identifies refined copy number and expression subtypes","year":2024,"lang":"en","type":"article","venue":"Nature Genetics","topic":"Multiple Myeloma Research and Treatments","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Alberta Cancer Foundation; Royal Victoria Hospital; Princess Margaret Cancer Centre","funders":"Principia Biopharma; Legend Biotech; Pharmacyclics; Kite Pharma; Genentech; EMD Serono; MorphoSys; Seagen; BeiGene; SkylineDx; Moderna; Pfizer; Incyte; Astex Pharmaceuticals; Baxalta; TG Therapeutics; Daewoong Pharmaceutical Company; Regeneron Pharmaceuticals; Eli Lilly and Company; AstraZeneca; CSL Behring; Swedish Orphan Biovitrum; Novo Nordisk; Teva Pharmaceutical Industries; Array BioPharma; National Cancer Institute; Gilead Sciences; Sanofi; Amgen; Vifor Pharma; Multiple Myeloma Research Foundation","keywords":"Biology; Multiple myeloma; Gene expression profiling; Computational biology; Profiling (computer programming); Expression (computer science); Genetics; Gene expression; Gene; Immunology; Computer science","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":[0.000500903,0.0002186071,0.0003397755,0.0009403389,0.000296787,0.0006908848,0.0002756762,0.0003360932,0.001392609],"category_scores_gemma":[0.001103603,0.0001749774,0.0003160013,0.0009695728,0.0001937814,0.0002241401,0.0004998408,0.0004971151,0.0004134359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003559223,"about_ca_system_score_gemma":0.0002415958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002055243,"about_ca_topic_score_gemma":0.003698586,"domain_scores_codex":[0.9996414,0.00003375158,0.00002451184,0.0001391131,0.0001051443,0.00005608976],"domain_scores_gemma":[0.9995714,0.00007449962,0.0001348191,0.00009654713,0.00007480198,0.00004791935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001139493,0.00008815012,0.6339487,0.00011309,0.0003428087,0.0003193332,0.0003115881,0.001768436,0.2916296,0.0007006893,0.001989752,0.06764847],"study_design_scores_gemma":[0.00003851929,0.0002047181,0.9608336,0.00001992924,0.0001260972,0.001306688,0.0001139606,0.002768544,0.02929706,0.0009644832,0.004305498,0.00002083675],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898401,0.0009123561,0.003536083,0.0001521628,0.000007521933,0.00003405016,0.004117395,0.0001112231,0.001289037],"genre_scores_gemma":[0.9919002,0.0003777913,0.003108363,0.0001156545,0.000008796069,0.00003385966,0.003447785,0.00003842232,0.0009693002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002055243,"threshold_uncertainty_score":0.004658699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01700704981119996,"score_gpt":0.3285415472476464,"score_spread":0.3115344974364465,"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."}}