{"id":"W4385983130","doi":"10.1016/j.exphem.2023.06.130","title":"3023 – ATLAS-AML: AN AUTOMATED BIOINFORMATICS PIPELINE FOR TARGET CHARACTERIZATION IN ACUTE MYELOID LEUKEMIA","year":2023,"lang":"en","type":"article","venue":"Experimental Hematology","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network","funders":"","keywords":"Myeloid leukemia; Transcriptome; Computational biology; Bioinformatics; Leukemia; Myeloid; Atlas (anatomy); Biology; Cancer research; Medicine; Gene; Immunology; Gene expression; 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":[0.002044174,0.002279991,0.001917006,0.003239481,0.001195489,0.002942056,0.002010334,0.001195222,0.01990457],"category_scores_gemma":[0.005573933,0.001047286,0.001924102,0.002519505,0.0004535509,0.001349768,0.002393211,0.001695244,0.01639643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001262795,"about_ca_system_score_gemma":0.004392251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005534282,"about_ca_topic_score_gemma":0.009799414,"domain_scores_codex":[0.9985423,0.0003061743,0.0001556913,0.0004740226,0.0003865401,0.0001353063],"domain_scores_gemma":[0.9985355,0.0006650519,0.000144545,0.000253976,0.0002801976,0.0001207919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003536716,0.0003517868,0.01563415,0.003444997,0.001801131,0.0009568327,0.0005656061,0.01980739,0.08006708,0.0100886,0.6200936,0.2436521],"study_design_scores_gemma":[0.001394936,0.0005431872,0.01654769,0.0002280549,0.0008872562,0.001920962,0.0001988391,0.1543873,0.121456,0.03225736,0.669856,0.0003224705],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.03387196,0.004871065,0.2527761,0.001673739,0.0005073167,0.0007224224,0.2446269,0.4477019,0.01324871],"genre_scores_gemma":[0.1250443,0.002602321,0.4006869,0.002318637,0.0003010688,0.002214676,0.4330846,0.02266406,0.01108341],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.01990457,"threshold_uncertainty_score":0.06658745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02483181063886628,"score_gpt":0.3559312414755823,"score_spread":0.331099430836716,"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."}}