{"id":"W4393454462","doi":"10.5281/zenodo.2718713","title":"CRISPR knockout of EZH1 in AML cell line","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre; University Health Network","funders":"","keywords":"CRISPR; Line (geometry); Computational biology; Biology; Genetics; Gene; Mathematics","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":[0.001047433,0.001566846,0.001988284,0.002606096,0.0009920222,0.001879036,0.002477889,0.002024054,0.06803996],"category_scores_gemma":[0.003411104,0.0006266781,0.001196924,0.003912792,0.0003411571,0.0007653608,0.001447727,0.001988391,0.04945495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170066,"about_ca_system_score_gemma":0.002208506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008278865,"about_ca_topic_score_gemma":0.02121093,"domain_scores_codex":[0.999046,0.0001170302,0.0001151495,0.0003020732,0.000271178,0.0001485026],"domain_scores_gemma":[0.9986565,0.000474552,0.0001321711,0.0003539736,0.0001726804,0.0002101906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006201739,0.00009207871,0.004703353,0.003199302,0.0003389757,0.0002322596,0.00007531395,0.001880006,0.006585893,0.00179319,0.971128,0.009351376],"study_design_scores_gemma":[0.001207743,0.0001323487,0.0101136,0.0003939148,0.0003164328,0.0004001505,0.0001006911,0.001224254,0.008001766,0.002737867,0.9752876,0.00008374086],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006500269,0.0001239418,0.0001771875,0.00007225032,0.00002287661,0.0000159621,0.9977508,0.0004947877,0.0006921137],"genre_scores_gemma":[0.001197155,0.0001042022,0.0005839896,0.00009012035,0.000003005567,0.0001306684,0.9971676,0.0001245023,0.0005986994],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06803996,"threshold_uncertainty_score":0.2276163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03096399986579517,"score_gpt":0.2978565861446088,"score_spread":0.2668925862788136,"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."}}