{"id":"W4377093091","doi":"10.1002/ajh.26935","title":"Comprehensive profiling of clinical <scp>JAK</scp> inhibitors in myeloproliferative neoplasms","year":2023,"lang":"en","type":"article","venue":"American Journal of Hematology","topic":"Myeloproliferative Neoplasms: Diagnosis and Treatment","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Heart, Lung, and Blood Institute; National Cancer Institute; MPN Research Foundation; National Institutes of Health; Alvin J. Siteman Cancer Center; Institute of Clinical and Translational Sciences; Canadian Institutes of Health Research; Leukemia and Lymphoma Society","keywords":"Ruxolitinib; Myeloproliferative neoplasm; Cancer research; Janus kinase; STAT3; stat; Myelofibrosis; Biology; Medicine; Pharmacology; Cytokine; Signal transduction; Immunology; Bone marrow; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002318135,0.0002222309,0.0003362669,0.0008842596,0.0002007649,0.0005547257,0.0001137528,0.0002067554,0.0008647174],"category_scores_gemma":[0.0002841233,0.00007601,0.0001743384,0.0007802073,0.0001374467,0.0001458825,0.0001523105,0.0002960996,0.0003322689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002486889,"about_ca_system_score_gemma":0.0004024175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000456441,"about_ca_topic_score_gemma":0.001324209,"domain_scores_codex":[0.9997712,0.00002127217,0.00001797313,0.00004749915,0.0001028515,0.00003916952],"domain_scores_gemma":[0.9998356,0.00003214139,0.00005313602,0.00001087548,0.00004178588,0.00002635284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0007178346,0.0001215541,0.04141638,0.0003051191,0.00009977486,0.0003569686,0.00006883733,0.001453327,0.8975908,0.0002788611,0.00159978,0.05599081],"study_design_scores_gemma":[0.00006079604,0.001551764,0.3466531,0.00008147592,0.0003649243,0.004103428,0.0002703044,0.005613741,0.5936252,0.0005978221,0.04704604,0.00003147477],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9749908,0.0075095,0.003567616,0.0003006168,0.00002522116,0.0001347134,0.008930117,0.000181724,0.004359677],"genre_scores_gemma":[0.9743947,0.004852204,0.005700986,0.0003032321,0.00003528313,0.0001391086,0.0120985,0.0000449997,0.002430967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008842596,"threshold_uncertainty_score":0.002892733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04216840408838109,"score_gpt":0.3690324555668604,"score_spread":0.3268640514784793,"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."}}