{"id":"W2947940526","doi":"10.1016/j.exphem.2019.05.003","title":"Pediatric leukemia: Moving toward more accurate models","year":2019,"lang":"en","type":"review","venue":"Experimental Hematology","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Hôpital de l'Enfant-Jésus; Université de Montréal; Centre hospitalier universitaire de Québec; Institute for Research in Immunology and Cancer","funders":"Canadian Cancer Society Research Institute","keywords":"Leukemia; Computer science; Medicine; Computational biology; Internal medicine; Biology","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002408017,0.0009664334,0.004511415,0.000729661,0.0001053827,0.00004186669,0.0007056526,0.001366143,0.0008020191],"category_scores_gemma":[0.00007478771,0.00078398,0.0009828657,0.0006283188,0.0001971719,0.0002213303,0.0008791981,0.001788462,0.00251322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002982239,"about_ca_system_score_gemma":0.003105239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000492158,"about_ca_topic_score_gemma":3.255563e-7,"domain_scores_codex":[0.9955471,0.0002357764,0.001199816,0.00125019,0.0006197845,0.00114734],"domain_scores_gemma":[0.9974723,0.0003307855,0.0004737725,0.001191565,0.00009560848,0.0004360055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007452299,0.001977972,0.0001222491,0.3829456,0.003834726,0.01532553,0.004154768,0.00004671437,0.0000543667,0.06766044,0.1427952,0.3803372],"study_design_scores_gemma":[0.004167227,0.0008105881,0.0000017299,0.008084218,0.002724428,0.02118378,0.001166345,0.001913904,0.001165801,0.0001033723,0.9565634,0.002115275],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000118337,0.9902744,0.0000934135,0.00008111763,0.0007356782,0.002523571,0.00004066712,0.0002165016,0.005916292],"genre_scores_gemma":[0.001036406,0.9936047,0.0008555577,0.0002402617,0.0006182622,0.0006035605,0.0004044644,0.0002752139,0.002361566],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8137681,"threshold_uncertainty_score":0.9999303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1284470145976232,"score_gpt":0.4224455466601128,"score_spread":0.2939985320624896,"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."}}