{"id":"W3044838252","doi":"10.3390/cancers12082002","title":"Targeting STAT3 and STAT5 in Cancer","year":2020,"lang":"en","type":"editorial","venue":"Cancers","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Research, Development and Innovation Office; Hungarian Scientific Research Fund; Canadian Institutes of Health Research; Austrian Science Fund","keywords":"Computational biology; Cancer; Human genome; Biology; Gene; Genome; Genetics; Cancer research","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00008427221,0.0002319731,0.000267943,0.00003695606,0.000035638,0.00004027005,0.000159388,0.0003979202,0.00002366279],"category_scores_gemma":[0.0003927572,0.0002615356,0.00004424442,0.00007184493,0.00007210521,0.000001819543,0.0001531382,0.0003276275,0.000002291885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004984845,"about_ca_system_score_gemma":0.002480823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002299909,"about_ca_topic_score_gemma":0.002056253,"domain_scores_codex":[0.9987664,0.00002197068,0.0002236223,0.0005403222,0.0001596383,0.0002880878],"domain_scores_gemma":[0.9994514,0.00005918782,0.000118675,0.000167929,0.00007625817,0.0001265514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000930517,0.000002669073,0.0002268311,0.00009709309,0.00003887946,0.00001039626,0.00008348929,0.001247961,0.003572604,0.000003752783,0.9932643,0.001359022],"study_design_scores_gemma":[0.0005706133,0.0001224698,0.00002483821,0.00005684412,0.00002314605,1.595452e-7,0.0000708326,0.00009060947,0.0007928291,0.00001962638,0.9979184,0.0003096799],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.01733988,0.0490268,0.0001046293,0.0002865218,0.9285977,0.0004651244,0.00345842,0.00001800978,0.0007029198],"genre_scores_gemma":[0.009711439,0.08225765,0.0002352195,0.0006121231,0.9044442,0.0001732727,0.001943826,0.0001176934,0.0005045399],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.03323085,"threshold_uncertainty_score":0.9999837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006864070484919944,"score_gpt":0.2646314888082739,"score_spread":0.257767418323354,"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."}}