{"id":"W4293427664","doi":"10.3389/fgene.2022.987238","title":"A p53 transcriptional signature in primary and metastatic cancers derived using machine learning","year":2022,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Cancer-related Molecular Pathways","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Common Fund; NIH Office of the Director; National Human Genome Research Institute; National Cancer Institute; BC Cancer Foundation; National Institutes of Health; Genome British Columbia; Genome Canada","keywords":"Gene; Biology; Transcriptome; Gene signature; Alternative splicing; RNA splicing; Transcriptional regulation; Suppressor; Cancer; Tumor suppressor gene; Transcription factor; Cancer research; Computational biology; Genetics; Gene expression; Messenger RNA; Carcinogenesis; RNA","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004613065,0.0003389202,0.0003778261,0.0007970116,0.0001610047,0.0003032384,0.0001536788,0.0002824056,0.0005119987],"category_scores_gemma":[0.0008438685,0.00007079195,0.0005744466,0.0005248612,0.0001332278,0.000144696,0.0001562764,0.0002610071,0.0002342287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002226561,"about_ca_system_score_gemma":0.0002445171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001492243,"about_ca_topic_score_gemma":0.001329255,"domain_scores_codex":[0.9998004,0.00003112699,0.00001336605,0.00006589704,0.00004235157,0.00004693322],"domain_scores_gemma":[0.9997205,0.0001262442,0.00004376907,0.00002389674,0.00005839175,0.00002713931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002040944,0.0004509336,0.212576,0.0003389945,0.0002719907,0.001262721,0.000250512,0.05635763,0.4332857,0.0005428918,0.001821877,0.2907997],"study_design_scores_gemma":[0.00005006099,0.001155192,0.2580009,0.0000518261,0.0002574226,0.001572887,0.000190082,0.60718,0.1270089,0.001866313,0.002611224,0.00005524472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9622951,0.0005164051,0.0352933,0.00007618552,0.00002623885,0.000045808,0.000817724,0.0004160959,0.0005131958],"genre_scores_gemma":[0.9811287,0.0001511369,0.01598578,0.00003284357,0.00001420182,0.00003198316,0.00219325,0.00002156047,0.0004406266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001492243,"threshold_uncertainty_score":0.002967179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01379449600945344,"score_gpt":0.2313842966710133,"score_spread":0.2175898006615599,"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."}}