{"id":"W2180291937","doi":"10.1016/j.cell.2015.11.015","title":"High-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities","year":2015,"lang":"en","type":"article","venue":"Cell","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1790,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Institute for Cancer Research; Canadian Institute for Advanced Research; Hospital for Sick Children; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; University of Toronto","funders":"Canadian Institutes of Health Research; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Biology; CRISPR; Gene; Computational biology; Genetics; Genetic Fitness; Context (archaeology); Cas9; Genome","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":[0.0003126888,0.0007306364,0.0006155809,0.0008062887,0.0004675851,0.001036255,0.0005176086,0.0008602631,0.004210975],"category_scores_gemma":[0.0004634541,0.0004258135,0.0005300269,0.0004983299,0.0006243563,0.0003163292,0.000937315,0.001557196,0.001224255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006135122,"about_ca_system_score_gemma":0.0003249965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001198321,"about_ca_topic_score_gemma":0.003561827,"domain_scores_codex":[0.9994562,0.00006739891,0.00005434104,0.000131775,0.0001975697,0.00009276414],"domain_scores_gemma":[0.999416,0.000252909,0.0001024818,0.0001069478,0.00004128795,0.00008041091],"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":[0.00002766401,0.00001595408,0.0002352217,0.00001732202,0.000008933286,0.0001065986,0.00001296485,0.0001947737,0.9976762,0.000337928,0.00009230964,0.001274136],"study_design_scores_gemma":[0.00001234817,0.00006382722,0.005502001,0.000005869632,0.00003274139,0.0006960344,0.00004256333,0.002048334,0.9883889,0.0002557643,0.002934021,0.00001749622],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.923817,0.001412309,0.05674054,0.0007705559,0.00008477792,0.0001204153,0.003910216,0.00232553,0.01081864],"genre_scores_gemma":[0.9814432,0.0004707913,0.008397273,0.0002589237,0.000008151651,0.00005151904,0.001151779,0.000477321,0.007741031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004210975,"threshold_uncertainty_score":0.01408714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01616619891226832,"score_gpt":0.2693357461505522,"score_spread":0.2531695472382838,"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."}}