{"id":"W4282980285","doi":"10.1038/s41586-022-04738-6","title":"Signatures of copy number alterations in human cancer","year":2022,"lang":"en","type":"article","venue":"Nature","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":516,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Medical Research Council; University of California, San Diego; Fonds De La Recherche Scientifique - FNRS; University College London; Wellcome Trust; Francis Crick Institute; National Institutes of Health; Cancer Research UK; National Institute of Environmental Health Sciences; National Institute for Health and Care Research; Sarcoma UK","keywords":"Chromothripsis; Biology; Copy-number variation; Copy number analysis; Genetics; Cancer; Computational biology; Genome instability; Human genome; Genome; DNA; Gene; DNA damage","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":[0.0002572477,0.0001821593,0.0003457208,0.001671287,0.0001561313,0.0004877392,0.0002627489,0.0002419362,0.001457448],"category_scores_gemma":[0.001293469,0.0001029779,0.0001797198,0.001665602,0.0002780636,0.0002625548,0.0003921326,0.0002034952,0.0002479366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003283047,"about_ca_system_score_gemma":0.0001496378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009741775,"about_ca_topic_score_gemma":0.001145385,"domain_scores_codex":[0.9996808,0.00003334457,0.00001795435,0.0001387316,0.00009910688,0.00003004243],"domain_scores_gemma":[0.9993597,0.0001815584,0.0002614742,0.00009154368,0.00006739407,0.00003828454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006194123,0.00004253721,0.5672946,0.0003235365,0.0003701737,0.000509358,0.0002344418,0.007507691,0.3370225,0.001997767,0.0009830669,0.08309481],"study_design_scores_gemma":[0.00001456706,0.0002295247,0.9254068,0.00002457641,0.0001831744,0.00283551,0.0001330221,0.01496528,0.04730321,0.004115045,0.004759621,0.00002956142],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9814622,0.0034858,0.009634271,0.0001118717,0.000008972021,0.00002784604,0.003365113,0.0001834886,0.00172034],"genre_scores_gemma":[0.9951435,0.0005414814,0.002521096,0.00004199949,0.000008824586,0.00002011281,0.001299039,0.00001481382,0.0004091204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001671287,"threshold_uncertainty_score":0.00487566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005260340953848212,"score_gpt":0.2892031712591475,"score_spread":0.2839428303052993,"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."}}