{"id":"W2561655537","doi":"10.1182/blood.v126.23.4973.4973","title":"Practical Acute Myeloid Leukemia (AML) Biomarker Testing Using Next-Generation Sequencing (NGS) Technology: A Comprehensive, Rapid, Inexpensive and Flexible Approach","year":2015,"lang":"en","type":"article","venue":"Blood","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences North","funders":"","keywords":"CEBPA; Computational biology; Minimal residual disease; Personalized medicine; NPM1; Biomarker; DNA sequencing; Myeloid leukemia; Biomarker discovery; Medicine; Bioinformatics; Oncology; Biology; Leukemia; Gene; Internal medicine; Genetics; Mutation; Proteomics; 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":[0.002151892,0.001366894,0.0008537149,0.001976466,0.0005039328,0.001533151,0.001105805,0.001414071,0.002483554],"category_scores_gemma":[0.001751504,0.0007806479,0.0007718351,0.0008517916,0.0007008514,0.001018703,0.001835303,0.001558685,0.002937494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004017446,"about_ca_system_score_gemma":0.00125799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007625769,"about_ca_topic_score_gemma":0.002081064,"domain_scores_codex":[0.9974744,0.0005605543,0.0002013697,0.0005525184,0.001098177,0.0001129336],"domain_scores_gemma":[0.9991534,0.0002087652,0.0001314408,0.0001455868,0.0002658799,0.00009487176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001604333,0.0001384314,0.005217994,0.000518319,0.00009705958,0.0003519895,0.0001546563,0.002981755,0.8426358,0.00151187,0.005051527,0.1411802],"study_design_scores_gemma":[0.00006511711,0.0005270896,0.01348157,0.000189983,0.0002340138,0.003715385,0.0002104076,0.04495078,0.8409369,0.004704853,0.09070237,0.0002815634],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0607063,0.004069071,0.9137712,0.001759595,0.0003651206,0.001748362,0.003611301,0.007497375,0.006471761],"genre_scores_gemma":[0.09963913,0.001951351,0.8890824,0.0008866786,0.000118443,0.0007569987,0.003550746,0.0002961825,0.003718042],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002483554,"threshold_uncertainty_score":0.01138043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2668825862060752,"score_gpt":0.3620575923762642,"score_spread":0.09517500617018904,"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."}}