{"id":"W2896929167","doi":"10.1007/978-1-4939-8805-1_15","title":"Pooled Lentiviral CRISPR-Cas9 Screens for Functional Genomics in Mammalian Cells","year":2018,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Institute for Advanced Research; University of Toronto","funders":"Canadian Institutes of Health Research; Canada Research Chairs; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"CRISPR; Functional genomics; Cas9; Gene knockout; Biology; Computational biology; Gene; Genome editing; Guide RNA; Genetic screen; Genomics; Drug discovery; Function (biology); Genetics; Phenotype; Genome; Bioinformatics","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":[0.001497775,0.001036069,0.001387689,0.00142838,0.0007715512,0.001454753,0.001323127,0.001126629,0.006394077],"category_scores_gemma":[0.0007356229,0.0008032913,0.001359943,0.0006601605,0.0005106226,0.0006157194,0.001439425,0.002152691,0.003391607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007896624,"about_ca_system_score_gemma":0.0008527971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001686996,"about_ca_topic_score_gemma":0.004118866,"domain_scores_codex":[0.9982384,0.0001366347,0.0002504647,0.0004092855,0.0007698358,0.0001953252],"domain_scores_gemma":[0.9993772,0.0001360638,0.00009600847,0.0001724369,0.0001202014,0.00009811807],"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":[0.00009240282,0.00005336031,0.0002177527,0.00006270154,0.00005400382,0.00009411188,0.00003033289,0.0001968651,0.9948069,0.0004358399,0.000321775,0.003634071],"study_design_scores_gemma":[0.00004667101,0.0001239148,0.001430778,0.0000113483,0.0001052262,0.000294263,0.00002377637,0.00173909,0.9888796,0.0002541982,0.007071706,0.00001941252],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5093881,0.00316897,0.4377804,0.00060317,0.0005408463,0.002379683,0.01688422,0.009333923,0.01992071],"genre_scores_gemma":[0.795463,0.00164522,0.1534923,0.0007730613,0.00008955134,0.001987148,0.01506472,0.002075863,0.0294091],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006394077,"threshold_uncertainty_score":0.02139038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02085657723877584,"score_gpt":0.4020531646386547,"score_spread":0.3811965873998789,"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."}}