{"id":"W3159627478","doi":"10.1101/2021.04.24.441206","title":"Single-cell landscapes of primary glioblastomas and matched organoids and cell lines reveal variable retention of inter- and intra-tumor heterogeneity","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Canada's Michael Smith Genome Sciences Centre; Genome British Columbia; University of British Columbia","funders":"BC Cancer Foundation; University of British Columbia; Terry Fox Research Institute; Canada Research Chairs; Killam Trusts; Genome British Columbia; Canadian Institutes of Health Research; Canada's Michael Smith Genome Sciences Centre; Genome Canada","keywords":"Genetic heterogeneity; Organoid; Transcriptome; Phenotype; Context (archaeology); Biology; Brain tumor; Tumor heterogeneity; Computational biology; Exome; Single-cell analysis; Gene; Cell; Cancer research; Genetics; Exome sequencing; Gene expression; Cancer; Pathology; Medicine","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":[0.0001244593,0.000125768,0.0002686234,0.0002941587,0.0001860359,0.0004704023,0.00009449829,0.0001944587,0.001026113],"category_scores_gemma":[0.0001618142,0.0001101617,0.0002043664,0.000434039,0.0001940116,0.0001938127,0.0003209702,0.0002580684,0.0004125308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002485702,"about_ca_system_score_gemma":0.0001468722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001201594,"about_ca_topic_score_gemma":0.001701863,"domain_scores_codex":[0.9998877,0.000007247161,0.000005691243,0.00004482119,0.00003313608,0.00002133346],"domain_scores_gemma":[0.9999001,0.00002445537,0.00001953534,0.00001879853,0.00001805499,0.00001906371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001476585,0.00001075863,0.008538021,0.00007305386,0.00003518502,0.00009198047,0.0001399241,0.0009103565,0.9848585,0.0002023164,0.0005152597,0.00447687],"study_design_scores_gemma":[0.0000137828,0.0001363175,0.3826547,0.00002757731,0.00008862784,0.001060574,0.000892576,0.01039452,0.5871047,0.001532326,0.01604792,0.00004633527],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817338,0.0006485475,0.0080734,0.00007523193,0.00001455414,0.000008026254,0.008061832,0.000195495,0.001189214],"genre_scores_gemma":[0.9754858,0.0005735848,0.005693961,0.00009387704,0.000006069009,0.0000327159,0.01674436,0.0001462945,0.001223401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001201594,"threshold_uncertainty_score":0.003432751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007318487446832046,"score_gpt":0.1861947674904782,"score_spread":0.1788762800436462,"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."}}