{"id":"W4394379135","doi":"10.6084/m9.figshare.12774957","title":"Additional file 8 of The RNA-binding protein SERBP1 functions as a novel oncogenic factor in glioblastoma by bridging cancer metabolism and epigenetic regulation","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; University of Toronto","funders":"","keywords":"Epigenetics; Glioblastoma; Bridging (networking); RNA-binding protein; Biology; RNA; Computational biology; Cancer research; Genetics; Bioinformatics; Gene; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001002809,0.001695647,0.001894885,0.002211252,0.0007585222,0.002196966,0.002261626,0.001811131,0.4693878],"category_scores_gemma":[0.009148838,0.0006619592,0.001636423,0.00365665,0.0003020119,0.00143787,0.001253871,0.001214045,0.104968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284434,"about_ca_system_score_gemma":0.001766003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008571846,"about_ca_topic_score_gemma":0.01664528,"domain_scores_codex":[0.999388,0.00008078314,0.00008545283,0.0002187068,0.0001198806,0.0001072985],"domain_scores_gemma":[0.9956647,0.002790011,0.0003264117,0.0003997662,0.0005811544,0.0002380954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003691129,0.0000499795,0.002557645,0.005392718,0.0001370726,0.00006482927,0.00003561503,0.000611941,0.0003985319,0.0006830075,0.985992,0.003707557],"study_design_scores_gemma":[0.003965219,0.0001333523,0.01977439,0.00242335,0.000371649,0.0003053401,0.0001365025,0.001270333,0.001484417,0.006251824,0.9637864,0.00009726802],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005454782,0.0000252621,0.00003328465,0.00002491508,0.000005557932,0.000007098074,0.9995893,0.000095053,0.0001650549],"genre_scores_gemma":[0.001109297,0.00007435727,0.0004144429,0.00009721555,0.0000106764,0.0001742365,0.997201,0.000151611,0.0007672911],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4693878,"threshold_uncertainty_score":0.7568539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0151817420259763,"score_gpt":0.2541875105762508,"score_spread":0.2390057685502745,"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."}}