{"id":"W3184895242","doi":"10.1038/s41375-021-01323-0","title":"Molecular landscape and prognostic impact of FLT3-ITD insertion site in acute myeloid leukemia: RATIFY study results","year":2021,"lang":"en","type":"article","venue":"Leukemia","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Alberta","funders":"National Cancer Institute; Astellas Pharma; Daiichi-Sankyo; Deutsche Forschungsgemeinschaft; MacroGenics; National Institutes of Health; Arog Pharmaceuticals; Astex Pharmaceuticals; Sunesis; Jazz Pharmaceuticals; Gilead Sciences; Daiichi Sankyo Europe; Sanofi; Celgene; Bristol-Myers Squibb; AstraZeneca; Amgen; Pfizer; Agios Pharmaceuticals","keywords":"Midostaurin; Myeloid leukemia; NPM1; Internal medicine; Oncology; Cumulative incidence; Fms-Like Tyrosine Kinase 3; Medicine; Leukemia; Transplantation; Biology; Mutation; Gene; Genetics","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":[0.002475371,0.0003278552,0.0006901284,0.0002653337,0.0001656777,0.0006712334,0.0003801394,0.0004557573,0.0009791445],"category_scores_gemma":[0.001960812,0.000150707,0.0007804939,0.000311534,0.0004615768,0.0004925761,0.0004404394,0.0005060661,0.0001804711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003900028,"about_ca_system_score_gemma":0.0003006783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003845186,"about_ca_topic_score_gemma":0.0009953068,"domain_scores_codex":[0.9991172,0.0003565903,0.00005966495,0.0001931178,0.0001644481,0.0001089534],"domain_scores_gemma":[0.9986154,0.0004376,0.0005306029,0.0001592881,0.00005520176,0.000201875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.04348115,0.0004869474,0.9044482,0.0001075893,0.000980742,0.0002037292,0.0001164324,0.00185947,0.01167943,0.0003573202,0.0007431344,0.03553585],"study_design_scores_gemma":[0.002951947,0.0137141,0.9719828,0.00002055791,0.001227663,0.0008141113,0.0001190998,0.002416735,0.003481066,0.000457261,0.002776595,0.0000380472],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990113,0.0003843789,0.00006738658,0.0000402874,0.000004520629,0.00000873245,0.0001620498,0.000003185979,0.0003181307],"genre_scores_gemma":[0.9987515,0.0001024768,0.000123541,0.00004100806,0.00002023235,0.00001185821,0.0007668914,0.000004077033,0.0001783138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002475371,"threshold_uncertainty_score":0.01309115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434078353816261,"score_gpt":0.3084374591255631,"score_spread":0.2940966755874005,"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."}}