{"id":"W4411410602","doi":"10.1371/journal.pone.0321761","title":"Machine learning driven dashboard for chronic myeloid leukemia prediction using protein sequences","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Princess Nourah Bint Abdulrahman University","keywords":"Support vector machine; Artificial intelligence; Computer science; Machine learning; Random forest; Dashboard; Decision tree; Data mining; Medicine; Database","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":[0.0001967036,0.0001514367,0.0001719435,0.00006947164,0.0002032952,0.00003928058,0.0001804639,0.0001597451,0.00001692826],"category_scores_gemma":[0.0003184839,0.0001522488,0.00006456365,0.0001069928,0.00006077913,0.000008733169,0.0001137606,0.0002193167,0.000005094113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001540453,"about_ca_system_score_gemma":0.0002673977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002798509,"about_ca_topic_score_gemma":0.00002064062,"domain_scores_codex":[0.9990526,0.00005410452,0.0002583967,0.0002396439,0.0001524393,0.0002428085],"domain_scores_gemma":[0.9994826,0.00001522389,0.0001326833,0.0002291304,0.00009966053,0.00004075764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005881846,0.00006691007,0.007108859,0.0004955333,0.0002266962,3.173813e-7,0.00004429727,0.008857379,0.9820219,0.0001157533,0.00007181797,0.0009316989],"study_design_scores_gemma":[0.0007879348,0.0005787365,0.0003272178,0.0003746643,0.0001281957,0.000002111077,0.00002426282,0.52644,0.4622551,0.00008663811,0.008785774,0.0002093463],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786138,0.0005085358,0.01786788,0.0001893775,0.00006130568,0.0008496931,0.00003799139,0.00008229327,0.001789117],"genre_scores_gemma":[0.9556065,0.0001137758,0.03864854,0.0001336149,0.0003324377,0.0001328894,0.0004613621,0.00002980847,0.00454107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5197668,"threshold_uncertainty_score":0.6208524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01942231184426383,"score_gpt":0.2502078489115112,"score_spread":0.2307855370672473,"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."}}