{"id":"W2950430797","doi":"10.1371/journal.pcbi.1006596","title":"Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer","year":2019,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Pancreatic and Hepatic Oncology Research","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; Princess Margaret Cancer Centre; University Health Network; University of Toronto; Ontario Institute for Cancer Research; Institute of Cancer Research","funders":"Canadian Institutes of Health Research; Ministero dello Sviluppo Economico; Hebrew University of Jerusalem; Government of Ontario; Ontario Institute for Cancer Research; Natural Sciences and Engineering Research Council of Canada; Princess Margaret Cancer Foundation","keywords":"Concordance; Copy-number variation; Biology; Tumour heterogeneity; Cancer; Computational biology; Organoid; Genome; Pancreatic cancer; Structural variation; Genetic heterogeneity; Metastasis; Cancer research; Gene; Genetics; Phenotype","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":[0.0006881442,0.0003017146,0.0004721415,0.001169754,0.0003313462,0.0007242503,0.0003175112,0.0004254127,0.001482921],"category_scores_gemma":[0.001867649,0.0003153879,0.0005024851,0.001134574,0.0002793228,0.0002101448,0.0009087828,0.0003983934,0.0003825146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005157182,"about_ca_system_score_gemma":0.0002933924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003176731,"about_ca_topic_score_gemma":0.006344694,"domain_scores_codex":[0.9992525,0.00009115753,0.0000532087,0.000306312,0.0002276522,0.00006913715],"domain_scores_gemma":[0.9990091,0.0003323054,0.0002682804,0.0002005755,0.0001162348,0.0000733819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001038981,0.00009336393,0.1072362,0.0002629015,0.000420061,0.0003536317,0.0006103039,0.009754283,0.8487858,0.0007768083,0.000821846,0.02984587],"study_design_scores_gemma":[0.00003725928,0.0005892036,0.6942626,0.00003059077,0.000378766,0.00208451,0.0003443001,0.03257804,0.2561033,0.001021923,0.01250308,0.00006635897],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782655,0.0003432044,0.01253804,0.00002956074,0.000009657635,0.00004654128,0.007110434,0.0003845241,0.001272565],"genre_scores_gemma":[0.9597051,0.0002761833,0.0123108,0.00005810034,0.000004522631,0.000105272,0.02630222,0.0002973998,0.0009404333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003176731,"threshold_uncertainty_score":0.006316483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03366654101948803,"score_gpt":0.3116270039085722,"score_spread":0.2779604628890842,"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."}}