{"id":"W2993515799","doi":"10.1038/s41586-019-1815-x","title":"The molecular landscape of ETMR at diagnosis and relapse","year":2019,"lang":"en","type":"article","venue":"Nature","topic":"Chromatin Remodeling and Cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":146,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children; University of Calgary; McGill University","funders":"National Center for Advancing Translational Sciences; National Institute of Environmental Health Sciences; National Cancer Institute; National Institutes of Health; Deutsche Krebshilfe; Bundesministerium für Bildung und Forschung; Russian Science Foundation; BeiGene; Deutsches Krebsforschungszentrum; Max and Minnie Tomerlin Voelcker Fund; Cancer Prevention and Research Institute of Texas; AstraZeneca","keywords":"Somatic cell; Genome instability; Germline; Biology; Mutation; Cancer research; Genetics; Genome; Chromosome instability; Gene; DNA; DNA damage; Chromosome","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":[0.0006476982,0.0001621041,0.0004027065,0.0009068849,0.0003543054,0.001441124,0.0005110927,0.0008623506,0.003565293],"category_scores_gemma":[0.001400296,0.000295337,0.0001914811,0.0007095081,0.0006640973,0.0009830433,0.0005967916,0.0008148716,0.0005645592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009145797,"about_ca_system_score_gemma":0.0004643345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001284152,"about_ca_topic_score_gemma":0.001481383,"domain_scores_codex":[0.9994388,0.0001184556,0.00002714843,0.0001095516,0.0001297899,0.0001762615],"domain_scores_gemma":[0.9995085,0.0001341458,0.0001680619,0.00003835695,0.00005451756,0.00009646697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003021357,0.0002776838,0.6522454,0.000240653,0.0002175196,0.003330039,0.0008411339,0.002826689,0.1208911,0.03133896,0.0117108,0.1730586],"study_design_scores_gemma":[0.00005026849,0.0003896244,0.9304118,0.0001013062,0.000101581,0.005249602,0.001121316,0.003416232,0.01430595,0.02251995,0.02227801,0.00005423369],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9340392,0.02873786,0.002431153,0.01488681,0.000152707,0.00003792089,0.001005757,0.0001538445,0.01855478],"genre_scores_gemma":[0.9954193,0.002005436,0.0002130705,0.0005442638,0.000124249,0.000009609956,0.0002578141,0.00001286495,0.001413546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003565293,"threshold_uncertainty_score":0.01192707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002584305990546613,"score_gpt":0.2287256412165645,"score_spread":0.2261413352260179,"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."}}