{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02565485,0.0006432903,0.001535887,0.003216897,0.001888203,0.006051605,0.002020069,0.00478447,0.002740471],"category_scores_gemma":[0.1144129,0.0003882944,0.00140879,0.001355829,0.003784755,0.005021205,0.00427413,0.009581266,0.001173017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00367853,"about_ca_system_score_gemma":0.005930049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002736705,"about_ca_topic_score_gemma":0.009188427,"domain_scores_codex":[0.9699941,0.01867505,0.004566948,0.0007652676,0.005293251,0.0007053899],"domain_scores_gemma":[0.9315442,0.05179693,0.004359943,0.001015039,0.009371096,0.001912745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001260486,0.0001029623,0.005068152,0.004816232,0.0002458942,0.0002035952,0.001608373,0.0003692541,0.000125798,0.009439816,0.5019953,0.4758985],"study_design_scores_gemma":[0.0001887475,0.0005000735,0.01052468,0.0349047,0.0006139271,0.001779954,0.005098598,0.001554322,0.0006029081,0.05512767,0.8888361,0.0002682867],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.005247877,0.1913924,0.01013553,0.7340178,0.0466017,0.0003921593,0.0003494117,0.0001347735,0.01172823],"genre_scores_gemma":[0.1517918,0.3652003,0.06153376,0.3361346,0.07615408,0.001160785,0.001053745,0.0003065809,0.006664242],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02565485,"threshold_uncertainty_score":0.1356775,"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."}}