{"id":"W4310554239","doi":"10.1016/j.compbiomed.2022.106372","title":"Quantifying imbalanced classification methods for leukemia detection","year":2022,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Lymphoblast; Artificial intelligence; Computer science; Lymphoblastic Leukemia; Leukemia; Machine learning; Deep learning; Class (philosophy); Pattern recognition (psychology); Biology; Immunology; Cell culture","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":[0.009740647,0.001299413,0.001344317,0.004594404,0.00108342,0.003361859,0.001645942,0.001887695,0.002108433],"category_scores_gemma":[0.02417778,0.0003520618,0.0006854923,0.002079809,0.0008506091,0.002778139,0.00220679,0.001281733,0.00115815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001414382,"about_ca_system_score_gemma":0.001039554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001481631,"about_ca_topic_score_gemma":0.001952353,"domain_scores_codex":[0.9942062,0.001235328,0.0004806009,0.000895444,0.002655954,0.0005264247],"domain_scores_gemma":[0.9848086,0.00745046,0.001535026,0.001528555,0.004261433,0.0004160366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002056075,0.0006506325,0.08747821,0.0005470821,0.0004360153,0.0002342509,0.000487886,0.07851464,0.03750625,0.01204437,0.01576215,0.7642823],"study_design_scores_gemma":[0.00006499046,0.0003148026,0.03322312,0.0000929253,0.0002065595,0.0004060122,0.0003323119,0.8983263,0.03251599,0.02543829,0.009010199,0.00006840991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2910359,0.004821989,0.6929852,0.001678661,0.0009337944,0.0003184205,0.001861219,0.001799476,0.004565404],"genre_scores_gemma":[0.8669905,0.0008017605,0.1238751,0.0003416254,0.0006175121,0.0001740514,0.002746378,0.00022681,0.004226286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009740647,"threshold_uncertainty_score":0.05151409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06868306947075617,"score_gpt":0.4111044714123605,"score_spread":0.3424214019416043,"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."}}