{"id":"W4405052057","doi":"10.1182/blood-2024-212361","title":"Demystifying Genomic and Transcriptomic Landscape of Acute Myeloid Leukaemia-Normal Karyotype Using Deep Sequencing Technology","year":2024,"lang":"en","type":"article","venue":"Blood","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Foothills Medical Centre","funders":"","keywords":"Karyotype; Myeloid leukaemia; Biology; Genetics; Deep sequencing; Computational biology; Transcriptome; Cancer research; Genome; Gene; Chromosome","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":[0.0003213642,0.0002528076,0.0003307428,0.000567023,0.0002209743,0.0004586803,0.0001797645,0.0002348775,0.0007805337],"category_scores_gemma":[0.0004525472,0.0001399839,0.00033335,0.0005153455,0.000152359,0.0001997209,0.0004851972,0.0004047028,0.0002198125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001962764,"about_ca_system_score_gemma":0.0002487217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006974383,"about_ca_topic_score_gemma":0.001767163,"domain_scores_codex":[0.9998069,0.00003421599,0.0000116959,0.00006932973,0.0000422323,0.00003565479],"domain_scores_gemma":[0.9998643,0.00004033103,0.00003433622,0.00001816995,0.00002778356,0.00001498372],"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":[0.0005635675,0.00007869053,0.09341511,0.0006172669,0.0003147885,0.0005506138,0.0006012826,0.003987888,0.8100678,0.001982165,0.002553456,0.0852674],"study_design_scores_gemma":[0.0000856185,0.0005926962,0.680276,0.0002018185,0.0006662125,0.002754675,0.001340732,0.06022544,0.1931803,0.01200513,0.04857805,0.00009336798],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9475743,0.003899687,0.03565088,0.0003432405,0.00004926669,0.00006631189,0.009872518,0.0002544464,0.002289393],"genre_scores_gemma":[0.9545061,0.001764745,0.02838953,0.000410304,0.00003263019,0.0001507016,0.01271392,0.00007995628,0.001952092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007805337,"threshold_uncertainty_score":0.002611101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02101900462722959,"score_gpt":0.280513974620799,"score_spread":0.2594949699935694,"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."}}