{"id":"W4407320257","doi":"10.1016/j.xcrm.2025.101964","title":"Unraveling AURKB as a potential therapeutic target in pulmonary hypertension using integrated transcriptomic analysis and pre-clinical studies","year":2025,"lang":"en","type":"article","venue":"Cell Reports Medicine","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval","keywords":"Transcriptome; Pulmonary hypertension; Medicine; Computer science; Computational biology; Medical physics; Internal medicine; Biology; Genetics; Gene expression; Gene","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":[],"consensus_categories":[],"category_scores_codex":[0.0005090312,0.0001296544,0.0003438333,0.0001728192,0.00006219572,0.000006564566,0.00005180582,0.0001190199,0.00001868764],"category_scores_gemma":[0.0001004812,0.00009685835,0.00008146272,0.0003642278,0.0001714608,0.000003166723,0.00002963409,0.0001180232,1.709416e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002105197,"about_ca_system_score_gemma":0.0001485835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002991917,"about_ca_topic_score_gemma":0.00003474431,"domain_scores_codex":[0.9987199,0.00007795331,0.0005436257,0.0004248023,0.00009628689,0.0001374395],"domain_scores_gemma":[0.9993878,0.00001700607,0.000129599,0.0002923398,0.0001264799,0.00004674666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000145905,0.0000968747,0.02660999,0.00003753053,0.0004536944,0.0001737496,0.00009170803,0.0005697764,0.9653807,0.000003814314,0.0001470047,0.006289258],"study_design_scores_gemma":[0.006113194,0.001426627,0.5261107,0.0011904,0.01051376,0.001032137,0.01119864,0.1039752,0.2900668,0.002804738,0.04391479,0.001653009],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9520679,0.03623543,0.0106163,0.0002780096,0.0003257397,0.0001607867,9.102372e-7,0.000007153844,0.0003077475],"genre_scores_gemma":[0.9937161,0.004344943,0.0002956136,0.0003988303,0.00008593887,0.000009842248,0.00006461149,0.000008761186,0.001075324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6753139,"threshold_uncertainty_score":0.3949769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02995115448783426,"score_gpt":0.3460932606159204,"score_spread":0.3161421061280861,"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."}}