{"id":"W4280581414","doi":"10.1016/j.leukres.2022.106858","title":"Genetic changes during leukemic transformation to secondary acute myeloid leukemia from myeloproliferative neoplasms","year":2022,"lang":"en","type":"article","venue":"Leukemia Research","topic":"Myeloproliferative Neoplasms: Diagnosis and Treatment","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre","funders":"National Research Foundation of Korea; Ministry of Health and Welfare; Ministry of Science, ICT and Future Planning; National Natural Science Foundation of China; Natural Sciences and Engineering Research Council of Canada; Princess Margaret Cancer Foundation","keywords":"Myeloid leukemia; Cancer research; Myeloid; Biology; Allele; Mutation; Myeloproliferative Disorders; Gene; Spliceosome; Malignant transformation; Internal medicine; Genetics; Oncology; Immunology; Medicine; RNA splicing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001328306,0.0001298631,0.0002238211,0.0007749515,0.0003167541,0.0003532151,0.0001786331,0.000250558,0.003409995],"category_scores_gemma":[0.0004194759,0.0001388556,0.0002455539,0.0003328796,0.0002176004,0.0001519307,0.0002405486,0.0003292086,0.0005403499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002760281,"about_ca_system_score_gemma":0.0001585535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009294513,"about_ca_topic_score_gemma":0.0008682746,"domain_scores_codex":[0.999832,0.00003713761,0.00001921433,0.00002980655,0.0000370666,0.00004478267],"domain_scores_gemma":[0.9997957,0.0000572232,0.00004547063,0.00001974238,0.00003061238,0.00005118206],"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":[0.001506741,0.0001990714,0.01201224,0.0000343525,0.00002872548,0.00219288,0.0001239182,0.0001271294,0.9767751,0.0006606033,0.000251166,0.006088113],"study_design_scores_gemma":[0.0001400869,0.001225987,0.3053797,0.00001204067,0.0001026501,0.01405294,0.0005101586,0.001356355,0.6679893,0.0005776696,0.008636467,0.00001663169],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967189,0.0003162157,0.0005060739,0.0000664687,0.00001419809,0.00003045008,0.0002749877,0.00003626034,0.002036459],"genre_scores_gemma":[0.9982749,0.0001613953,0.0001581145,0.00002607565,0.000005773657,0.000009449091,0.0003700243,0.00001269321,0.000981598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003409995,"threshold_uncertainty_score":0.01140755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03371642877177031,"score_gpt":0.3219601277074716,"score_spread":0.2882436989357012,"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."}}