{"id":"W4282939680","doi":"10.1158/1538-7445.am2022-6108","title":"Abstract 6108: <i>In vivo</i> CRISPR screens identified dual function of MEN1-MLL1 in regulating tumor-microenvironment interactions","year":2022,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto","funders":"","keywords":"Biology; Epigenetics; Cancer research; In vivo; CRISPR; Tumor microenvironment; Chromatin; Gene knockout; Cancer; Cell biology; Genetics; Gene","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":[0.0002780426,0.0006851854,0.0004369846,0.0003326829,0.0001769932,0.00036351,0.0003174476,0.0003958996,0.00366503],"category_scores_gemma":[0.0001511767,0.0001698193,0.0003429632,0.0001787614,0.0003047934,0.0001589713,0.0003399951,0.0006276709,0.001016013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003828337,"about_ca_system_score_gemma":0.000312117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008931375,"about_ca_topic_score_gemma":0.001556046,"domain_scores_codex":[0.9997249,0.00003528196,0.00002884412,0.00007950488,0.00009166556,0.00003977389],"domain_scores_gemma":[0.9997783,0.00004925388,0.00007830333,0.00002338757,0.00002210879,0.00004860852],"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":[0.00003901568,0.00001048281,0.0001585749,0.00002872017,0.000004878897,0.00006436383,0.000006557852,0.00009998772,0.9987129,0.00006064117,0.00007775475,0.0007361279],"study_design_scores_gemma":[0.00000533281,0.0001165731,0.001501683,0.000003630368,0.00001526289,0.0002487159,0.000007779428,0.0004427361,0.9959874,0.00002455246,0.001642746,0.000003597138],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9447396,0.001533812,0.03515197,0.0004424549,0.00008299448,0.0002115859,0.007961771,0.001638142,0.008237651],"genre_scores_gemma":[0.9709038,0.0007660448,0.01359404,0.000247356,0.00001276122,0.00008650834,0.0045378,0.000293738,0.009557951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00366503,"threshold_uncertainty_score":0.01226074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03642152940241653,"score_gpt":0.3452212314158333,"score_spread":0.3087997020134168,"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."}}