{"id":"W2055451826","doi":"10.1016/j.canlet.2006.10.012","title":"Identification of PEG10 as a progression related biomarker for hepatocellular carcinoma","year":2006,"lang":"en","type":"article","venue":"Cancer Letters","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Biology; Hepatocellular carcinoma; Comparative genomic hybridization; HCCS; Candidate gene; Gene; Cancer research; Biomarker; Microarray; Copy-number variation; Microarray analysis techniques; Gene expression; Gene expression profiling; Population; Genetics; Complementary DNA; Genome; Computational biology; Medicine","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":[0.0003419748,0.0003472849,0.0002697424,0.001132108,0.0001949986,0.0005063665,0.0002816114,0.0006003238,0.002240603],"category_scores_gemma":[0.001002584,0.0001766724,0.0001924608,0.0004065832,0.0002915915,0.0003487472,0.0003023256,0.0004638064,0.0005710805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000378273,"about_ca_system_score_gemma":0.000212548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007666214,"about_ca_topic_score_gemma":0.0004887212,"domain_scores_codex":[0.9998376,0.00004805258,0.00001363215,0.00002719985,0.00004026807,0.00003316344],"domain_scores_gemma":[0.9996489,0.0001091718,0.00005369843,0.00003425469,0.00006104753,0.00009291679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005077255,0.0003143238,0.1783753,0.0001531376,0.0001119751,0.003088649,0.0001116494,0.0005511969,0.7637057,0.0006718215,0.001377156,0.04646184],"study_design_scores_gemma":[0.0002445131,0.002411127,0.373644,0.00003323236,0.000173576,0.0156581,0.0002545347,0.01188634,0.5811031,0.001689592,0.0128596,0.0000421885],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916147,0.00145751,0.002429991,0.0005682962,0.0000715055,0.00004350433,0.0002816867,0.00008270684,0.003450125],"genre_scores_gemma":[0.9961176,0.000316264,0.001802452,0.0001009799,0.00003574325,0.00002107941,0.0003475644,0.000009438747,0.001248838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002240603,"threshold_uncertainty_score":0.007495522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007858131024098144,"score_gpt":0.2448499992292478,"score_spread":0.2369918682051497,"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."}}