{"id":"W4399318880","doi":"10.1016/j.celrep.2024.114260","title":"Immunotherapeutic targeting of surfaceome heterogeneity in AML","year":2024,"lang":"en","type":"article","venue":"Cell Reports","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network; Centre Hospitalier Universitaire Sainte-Justine; Princess Margaret Cancer Centre; Centre hospitalier universitaire de Québec; Hôpital Maisonneuve-Rosemont; Université Laval; Université de Montréal; Institute for Research in Immunology and Cancer","funders":"Fonds de Recherche du Québec - Santé; Institut de Valorisation des Données; Canada First Research Excellence Fund; Université de Montréal; Government of Canada; Génome Québec; Canadian Institutes of Health Research; Alliance de recherche numérique du Canada; Genome Canada","keywords":"Immunotherapy; Myeloid leukemia; Antigen; Biology; Computational biology; Myeloid; Population; Cancer immunotherapy; Antibody; Immunology; Cancer research; Medicine; Immune system","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":[0.0001174778,0.0001451136,0.0001862245,0.0002454954,0.000139731,0.0003331145,0.00008671272,0.0001442531,0.0005662887],"category_scores_gemma":[0.000125069,0.00006790883,0.0001387368,0.0001996366,0.0001746124,0.0002158592,0.0003226019,0.0002771835,0.0001177401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001745019,"about_ca_system_score_gemma":0.0001463626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001631222,"about_ca_topic_score_gemma":0.0003641828,"domain_scores_codex":[0.9999305,0.00001146231,0.000003280913,0.00001498426,0.00002152481,0.00001812171],"domain_scores_gemma":[0.9999641,0.000006809936,0.00001227375,0.000005645501,0.000004866234,0.000006278749],"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":[0.00004709098,0.00001088023,0.002096443,0.00002850041,0.000005494544,0.00003581823,0.00002286936,0.0001786727,0.9902503,0.0001659194,0.00006275173,0.007095214],"study_design_scores_gemma":[0.00001466278,0.0003398201,0.07785919,0.00001566022,0.00005325842,0.001042262,0.0002110809,0.004880365,0.901639,0.001140968,0.01279477,0.000008881534],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930882,0.001393456,0.004449666,0.0001327277,0.000009937487,0.00002240588,0.0001483744,0.00004588803,0.0007091982],"genre_scores_gemma":[0.9955353,0.001254408,0.002358204,0.00006665564,0.000009848741,0.00001610085,0.0002199398,0.00001169784,0.0005278972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005662887,"threshold_uncertainty_score":0.001894355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02077433823775421,"score_gpt":0.3075682404253691,"score_spread":0.2867939021876149,"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."}}