{"id":"W7117489209","doi":"10.1038/s41598-025-28551-z","title":"Multi-omics and machine learning refine HCC molecular subtypes and prognosis based on liquid–liquid phase separation related genes","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pancreas Centre (Canada)","funders":"National Natural Science Foundation of China","keywords":"Cluster analysis; Consensus clustering; Hepatocellular carcinoma; Ensemble learning; Support vector machine; Gene signature; Signature (topology)","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":[0.001247829,0.000478243,0.0006192937,0.001812192,0.0002625971,0.001025898,0.0002271094,0.0003731692,0.0008458973],"category_scores_gemma":[0.001460736,0.0001182098,0.0007125156,0.001465414,0.0002918766,0.0004988855,0.0005090422,0.0005123827,0.0002377076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004783752,"about_ca_system_score_gemma":0.0005243646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001448596,"about_ca_topic_score_gemma":0.001762515,"domain_scores_codex":[0.9995524,0.0001324386,0.00004001926,0.0001061449,0.00009833332,0.00007066882],"domain_scores_gemma":[0.9994129,0.0001844757,0.0001860597,0.00007048142,0.00009963608,0.00004650915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001637914,0.0002413969,0.6951753,0.0002317447,0.0005985494,0.0003291779,0.0002009426,0.02716568,0.1316142,0.001345753,0.001177108,0.1402821],"study_design_scores_gemma":[0.00006152604,0.000397841,0.6200448,0.0000886549,0.000742052,0.0006554066,0.0004675058,0.3104474,0.05629664,0.006846488,0.003867072,0.00008463432],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9671368,0.001760831,0.02817594,0.0003338918,0.00002384325,0.00005275077,0.001078214,0.0001945077,0.001243168],"genre_scores_gemma":[0.9893478,0.0002602741,0.009159242,0.00007034525,0.00001576077,0.00002748965,0.0008403137,0.00001963969,0.0002589814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001812192,"threshold_uncertainty_score":0.006599188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280707480316204,"score_gpt":0.304611258841242,"score_spread":0.29180418403808,"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."}}