{"id":"W4282971516","doi":"10.1158/1538-7445.am2022-6397","title":"Abstract 6397: Understanding the glioblastoma microenvironment with spatial resolution in PDX models","year":2022,"lang":"en","type":"article","venue":"Cancer Research","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Tumor microenvironment; Phenotype; Biology; Transcriptome; Cancer research; Genetic heterogeneity; Glioblastoma; Disease; Tumour heterogeneity; In vivo; Cancer; Pathology; Gene; Medicine; Genetics; Gene expression; Tumor cells","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":[0.0004715933,0.0004932563,0.0004473048,0.0003411657,0.000237039,0.0006085444,0.0006215477,0.0005507935,0.001153213],"category_scores_gemma":[0.0005727008,0.0002432827,0.0006354798,0.0003521159,0.0002917414,0.0002863792,0.0003621895,0.0006759981,0.0002569467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000570407,"about_ca_system_score_gemma":0.000590865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008478482,"about_ca_topic_score_gemma":0.007659367,"domain_scores_codex":[0.9998902,0.00002288539,0.000004723405,0.00004170977,0.00002508554,0.00001540957],"domain_scores_gemma":[0.9998624,0.0000730247,0.0000194577,0.00001197613,0.00001923619,0.00001395375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002436216,0.0001926364,0.008066511,0.0001668514,0.00009928343,0.0001555395,0.0000882391,0.8905323,0.08468813,0.002441473,0.001325605,0.01199977],"study_design_scores_gemma":[0.000008249338,0.00003486987,0.001496739,0.000002396796,0.000006451434,0.00001303651,0.00001974212,0.9926628,0.004461443,0.0007357349,0.0005510132,0.000007502474],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8020093,0.0002970856,0.1879071,0.0003188995,0.00004070289,0.00008843918,0.005353802,0.002112716,0.001871916],"genre_scores_gemma":[0.830173,0.0003011936,0.1585242,0.0001383877,0.00002092713,0.0002558234,0.008870893,0.0004841642,0.001231516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008478482,"threshold_uncertainty_score":0.01685828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08017802225159629,"score_gpt":0.3082241421398284,"score_spread":0.2280461198882321,"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."}}