{"id":"W2556190467","doi":"10.1016/j.bcmd.2016.11.003","title":"Corrigendum to “High abundance of circulating megakaryocytic cells in chronic myeloid leukemia in Indian patients. Revisiting George Minot to re-interpret megakaryocytic maturation” [Blood Cell Mol. Dis. 60 (2016) 28–32]","year":2016,"lang":"en","type":"erratum","venue":"Blood Cells Molecules and Diseases","topic":"Chronic Lymphocytic Leukemia Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"George (robot); Myeloid leukemia; Myeloid; Immunology; Medicine; Cancer research; Biology; History","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003999863,0.001226145,0.002152385,0.001336042,0.0001649183,0.0001768282,0.0008102306,0.000754204,0.0001670157],"category_scores_gemma":[0.0006076426,0.001109743,0.0004151327,0.001099409,0.0002452639,0.0002531678,0.0008520082,0.001048233,0.00009742026],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01352405,"about_ca_system_score_gemma":0.01702077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003330095,"about_ca_topic_score_gemma":0.0004779365,"domain_scores_codex":[0.9920657,0.0003362284,0.002098782,0.002080756,0.001564213,0.001854366],"domain_scores_gemma":[0.9956657,0.0003795188,0.0006461394,0.001561651,0.000383551,0.001363495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0109736,0.00834172,0.01328986,0.1293576,0.002947207,0.03721834,0.01346789,0.004932495,0.3548899,0.0002909555,0.4007774,0.02351308],"study_design_scores_gemma":[0.2051503,0.01375945,0.06002769,0.1868841,0.01072334,0.0005384759,0.00309434,0.01798453,0.4443637,0.0006431167,0.04088794,0.01594301],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9694223,0.01700306,0.00006983028,0.0001735202,0.00338726,0.004603661,0.001849718,0.0001096112,0.003381035],"genre_scores_gemma":[0.9801074,0.002651562,0.0004474604,0.0006407682,0.001261971,0.0003323305,0.001017041,0.0003118538,0.01322967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3598894,"threshold_uncertainty_score":0.9991353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007288052522072548,"score_gpt":0.2374115465286298,"score_spread":0.2301234940065573,"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."}}