{"id":"W4410029978","doi":"10.1182/bloodadvances.2025016114","title":"Finding the right fit: assessment of fitness in AML","year":2025,"lang":"en","type":"article","venue":"Blood Advances","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre; University of British Columbia","funders":"","keywords":"Medicine; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003419421,0.00008788997,0.0002402547,0.0001551537,0.0000566407,0.000009010626,0.0001982306,0.00004335132,0.0001046714],"category_scores_gemma":[0.0001603503,0.0000537082,0.00004853736,0.00053531,0.0001184625,0.00008451931,0.00008923568,0.0002743227,0.000003317239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000846551,"about_ca_system_score_gemma":0.000316602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000346155,"about_ca_topic_score_gemma":0.00007231796,"domain_scores_codex":[0.9990654,0.00005697913,0.0002344313,0.0001777001,0.0002495347,0.0002159337],"domain_scores_gemma":[0.9992227,0.0003429202,0.00005711729,0.0002868667,0.00005978066,0.00003064145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000201953,0.001081636,0.8910046,0.001299747,0.0003444461,0.0003025849,0.0005437912,0.0005540792,0.02029297,0.03054845,0.002656263,0.05116946],"study_design_scores_gemma":[0.007569427,0.0003454105,0.7922884,0.001385449,0.0002272697,0.00003780529,0.001120272,0.002189783,0.09182395,0.003409578,0.09936409,0.0002386387],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9379734,0.003556175,0.0003160861,0.005109037,0.000173042,0.0005758021,0.000009582684,0.00002767873,0.05225917],"genre_scores_gemma":[0.9942417,0.0004564128,0.001759423,0.0002241857,0.00004936915,0.00004970671,0.000004879394,0.000006934274,0.003207345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09871629,"threshold_uncertainty_score":0.2190157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01891390989027064,"score_gpt":0.3748222995840976,"score_spread":0.3559083896938269,"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."}}