{"id":"W4377086571","doi":"10.1016/j.cels.2023.04.003","title":"Reproducibility metrics for context-specific CRISPR screens","year":2023,"lang":"en","type":"article","venue":"Cell Systems","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Ontario Institute for Cancer Research","funders":"Canadian Institutes of Health Research; Hospital for Sick Children; Ontario Research Foundation; Canada Research Chairs; National Human Genome Research Institute; GlaxoSmithKline; National Institutes of Health; National Science Foundation","keywords":"CRISPR; Reproducibility; Context (archaeology); Computational biology; Computer science; Biology; Genetics; Mathematics; Statistics; Gene","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":[0.0008672239,0.0001247933,0.0001614392,0.00006702924,0.00007202983,0.00003037287,0.0001579173,0.0001133261,0.000003037256],"category_scores_gemma":[0.0002204009,0.0001233611,0.0001074569,0.0002412022,0.00002351634,0.000001401161,0.00006519085,0.00004685772,0.00003601259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001186619,"about_ca_system_score_gemma":0.0000244168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003640808,"about_ca_topic_score_gemma":0.000007690005,"domain_scores_codex":[0.9986187,0.00002844016,0.0002382622,0.0007442606,0.0001028944,0.0002675066],"domain_scores_gemma":[0.9986488,0.0000336945,0.00004516784,0.001074764,0.0001212614,0.00007630792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004781668,0.00004651089,0.001814525,0.0003451315,0.00004439757,0.000003515105,0.00009508101,0.00280881,0.8191437,0.0002360341,0.1708494,0.004565028],"study_design_scores_gemma":[0.0003898419,0.0001158821,0.0008332579,0.000009575082,0.00001028601,0.000003757862,0.0003918625,0.001326284,0.319568,0.00001230164,0.6771525,0.0001864654],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7699053,0.0285656,0.1914965,0.0001713584,0.0036004,0.00190393,0.0001734623,0.0002282525,0.003955185],"genre_scores_gemma":[0.9927936,0.0002617794,0.0001733514,0.00002426894,0.0006196436,0.00008786749,0.0001516681,0.00003177784,0.005856003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.506303,"threshold_uncertainty_score":0.5030518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03097819966375175,"score_gpt":0.3099705553019095,"score_spread":0.2789923556381577,"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."}}