{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007816498,0.0001088823,0.000267246,0.0001792568,0.0000161193,0.00001511287,0.00005202612,0.00008811032,0.000160866],"category_scores_gemma":[0.00007735869,0.00009268174,0.0001032607,0.000363275,0.00006241882,0.0000523965,0.00005429441,0.0003070426,0.00004086685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002310672,"about_ca_system_score_gemma":0.0003692158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001451548,"about_ca_topic_score_gemma":0.000006372098,"domain_scores_codex":[0.9986026,0.00004069259,0.0004880527,0.0003008291,0.0002949032,0.0002728786],"domain_scores_gemma":[0.999367,0.00007637215,0.00007033839,0.0003717203,0.00004266587,0.00007189755],"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":[0.00005506672,0.000107577,0.06614973,0.000725742,0.000061831,0.0110938,0.0004233338,0.00005554688,0.916622,0.000005491344,0.00135999,0.00333985],"study_design_scores_gemma":[0.0005651668,0.0001752568,0.02695379,0.0003971751,0.00005413718,0.001328689,0.0001200772,0.001498909,0.9246677,0.0002091846,0.04382395,0.000205973],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831517,0.009225656,0.00004881609,0.0001700488,0.0002182378,0.0002742889,0.000001084862,0.00005958428,0.006850623],"genre_scores_gemma":[0.9964736,0.0002284218,0.0004132515,0.00005307361,0.00004883899,0.000009846824,0.0000153731,0.00003471175,0.002722892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04246396,"threshold_uncertainty_score":0.3779452,"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."}}