{"id":"W2563350344","doi":"10.1038/srep39294","title":"Identification of cancer risk lncRNAs and cancer risk pathways regulated by cancer risk lncRNAs based on genome sequencing data in human cancers","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada","funders":"Natural Science Foundation of Heilongjiang Province; National Natural Science Foundation of China; Harbin Applied Technology Research and Development Project","keywords":"Cancer; Identification (biology); Genome; Computational biology; Human genome; Biology; Cancer genome sequencing; DNA sequencing; Bioinformatics; Genetics; Gene","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00303525,0.0003573257,0.0003868687,0.0003380855,0.0004754682,0.0001376957,0.0005902682,0.000314044,0.0001817993],"category_scores_gemma":[0.000502662,0.0003045304,0.0001069785,0.0006813681,0.0005251431,0.00004184075,0.0003454802,0.0003464318,0.000002384283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008409409,"about_ca_system_score_gemma":0.001623812,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0298037,"about_ca_topic_score_gemma":0.01719077,"domain_scores_codex":[0.9948849,0.0003600082,0.00102034,0.002154254,0.0009015308,0.00067893],"domain_scores_gemma":[0.9951576,0.00003323366,0.001452176,0.002692777,0.0004230894,0.0002411432],"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":[0.0001010287,0.0000409844,0.009769928,0.00004441601,0.0001178745,0.0000262893,0.00009267665,0.007311723,0.9708488,0.000003724481,0.002242492,0.009400068],"study_design_scores_gemma":[0.0009735057,0.0001015655,0.005077423,0.0002758568,0.0001224009,0.000007307797,0.00004935133,0.003724826,0.9776812,0.0003093741,0.01122437,0.000452892],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836825,0.008204546,0.002527769,0.0001227504,0.001538682,0.0008424255,0.002985955,0.00002917107,0.00006619279],"genre_scores_gemma":[0.9909996,0.00655909,0.00007589682,0.00002868801,0.0001286113,0.0002385275,0.0005782736,0.00007281492,0.00131852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01261292,"threshold_uncertainty_score":0.9999407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01918605225515802,"score_gpt":0.2972033707233158,"score_spread":0.2780173184681578,"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."}}