{"id":"W2971521058","doi":"10.3791/59780","title":"Pooled CRISPR-Based Genetic Screens in Mammalian Cells","year":2019,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"CRISPR; Computational biology; Genome editing; Biology; Genome; Genetic screen; Context (archaeology); Cas9; Functional genomics; Genomics; Gene; Genetics; Phenotype","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001819424,0.0001632085,0.0002507249,0.0001419849,0.00001611697,0.0000221361,0.0002155914,0.0001117066,0.0001454443],"category_scores_gemma":[0.00001888184,0.0001549705,0.0001493554,0.00009574756,0.00001812629,0.00000459745,0.0000438484,0.0001082362,0.00002368408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000284054,"about_ca_system_score_gemma":0.00007270505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001377516,"about_ca_topic_score_gemma":0.000002956079,"domain_scores_codex":[0.9988222,0.00006116513,0.0004564024,0.0001815755,0.0002274254,0.0002512766],"domain_scores_gemma":[0.9994025,0.000009029499,0.0001653352,0.0002311725,0.00007572999,0.000116204],"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":[0.0002186098,0.000137474,0.004532542,0.00001678242,0.00004149672,0.00002083788,0.00006702814,0.002754724,0.9913128,0.000003151902,0.0005688794,0.0003256441],"study_design_scores_gemma":[0.003139552,0.0005614284,0.006377359,0.00004730974,0.0000163258,0.00001784343,0.0001425161,0.0004236235,0.9822931,0.000005221912,0.006796114,0.0001796274],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891381,0.001875935,0.00811219,0.0000347957,0.0004262677,0.0001569117,0.000002823029,0.000003718849,0.0002492774],"genre_scores_gemma":[0.9929456,0.00006446824,0.00634475,0.0002242646,0.0001442612,0.000003912943,0.000005672392,0.00003036485,0.0002366877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009019751,"threshold_uncertainty_score":0.6319516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01119728441204107,"score_gpt":0.3914616672846215,"score_spread":0.3802643828725804,"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."}}