{"id":"W2519452348","doi":"10.1371/journal.pone.0162622","title":"Profiling of Small Nucleolar RNAs by Next Generation Sequencing: Potential New Players for Breast Cancer Prognosis","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Lethbridge; University of Alberta","funders":"","keywords":"Small nucleolar RNA; Biology; Breast cancer; Housekeeping gene; Computational biology; Proportional hazards model; Carcinogenesis; Long non-coding RNA; Confounding; Oncology; Bioinformatics; microRNA; Cancer; Genetics; Gene; RNA; Internal medicine; Medicine; Gene expression","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":[],"consensus_categories":[],"category_scores_codex":[0.0001281485,0.0001400063,0.0001640582,0.0000467553,0.00006096515,0.00002423891,0.0001737432,0.0001912534,0.00006833348],"category_scores_gemma":[0.00006795423,0.0001206337,0.00009015374,0.000074514,0.0000404882,0.000008508294,0.00006914102,0.00006777525,0.000003384343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008975216,"about_ca_system_score_gemma":0.0003819616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001197966,"about_ca_topic_score_gemma":0.00006086541,"domain_scores_codex":[0.9988105,0.00003622468,0.0002150521,0.0003802315,0.0002537313,0.0003043182],"domain_scores_gemma":[0.9992474,0.000006692824,0.0001063322,0.0002409215,0.0002738128,0.0001248229],"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":[0.0001948779,0.0001487071,0.00006366439,0.00006877341,0.0003121695,7.877005e-7,0.00001245264,0.00005296937,0.98979,0.00003477078,0.0008581891,0.008462613],"study_design_scores_gemma":[0.001005535,0.0002864896,0.0000137256,0.0001005252,0.0001006821,0.000003373988,0.00001292824,0.001972938,0.9960831,0.00002016355,0.0002365694,0.0001639556],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8570327,0.001097603,0.1393658,0.0009180622,0.00007556434,0.001027051,0.0004309332,0.00001985572,0.00003246214],"genre_scores_gemma":[0.9841086,0.0007040471,0.01302109,0.000114561,0.0005857846,0.0002189363,0.0001433663,0.00006254658,0.001041071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1270759,"threshold_uncertainty_score":0.49193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07811128529339438,"score_gpt":0.2617687978673649,"score_spread":0.1836575125739705,"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."}}