{"id":"W4225422943","doi":"10.1038/s41698-022-00268-6","title":"DNA-based copy number analysis confirms genomic evolution of PDX models","year":2022,"lang":"en","type":"article","venue":"npj Precision Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Congressionally Directed Medical Research Programs; Office of Research Infrastructure Programs, National Institutes of Health; National Cancer Institute; National Institutes of Health; V Foundation for Cancer Research; Israel Cancer Research Fund; Azrieli Foundation; Tel Aviv University; Israel Cancer Association","keywords":"Biology; Genetics; Genome; Genome instability; Somatic evolution in cancer; Genomics; Genome evolution; Cancer; Copy-number variation; Evolutionary biology; DNA; Computational biology; Gene; DNA damage","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004054031,0.0001344544,0.0003326038,0.0001380129,0.0001256417,0.000007956493,0.0002983532,0.000159301,0.000980568],"category_scores_gemma":[0.00007088924,0.0001468942,0.000243439,0.0003121341,0.00008386991,0.000002537584,0.0003030703,0.0001230343,0.00001634421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003025529,"about_ca_system_score_gemma":0.0005794619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001429539,"about_ca_topic_score_gemma":0.0001556673,"domain_scores_codex":[0.9986224,0.0001743472,0.0003861548,0.0004072259,0.0001920503,0.0002178892],"domain_scores_gemma":[0.9989427,0.0001231429,0.0002409536,0.0004747617,0.0001379232,0.00008054095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001683328,0.0007263832,0.02587201,0.00001407945,0.0006098977,0.00001231004,0.0001319064,0.5765109,0.366421,0.002530569,0.01567988,0.009807775],"study_design_scores_gemma":[0.00772622,0.005371893,0.02074973,0.00001011813,0.001499441,0.00005719905,0.0006274261,0.1133371,0.1409356,0.009138993,0.6994058,0.001140416],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9448988,0.0005702955,0.04899102,0.0001528139,0.0003823561,0.0002376006,0.000275046,0.000009226651,0.004482839],"genre_scores_gemma":[0.9969181,0.0001067956,0.001807256,0.000362316,0.00009316495,0.00007780573,0.0003224038,0.00001940243,0.0002927128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.683726,"threshold_uncertainty_score":0.9999326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01364918121091318,"score_gpt":0.2867721181321569,"score_spread":0.2731229369212437,"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."}}