{"id":"W3126460557","doi":"10.1016/j.ymeth.2021.01.005","title":"Production of knockout mouse lines with Cas9","year":2021,"lang":"en","type":"article","venue":"Methods","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; Toronto Centre for Phenogenomics","funders":"Canada Foundation for Innovation; Ontario Genomics","keywords":"Gene knockout; Knockout mouse; Germline; Biology; Transgene; CRISPR; Cas9; Genetics; Gene targeting; Gene; Cell biology; Electroporation; Computational biology","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":[0.00191777,0.001066839,0.001158442,0.001777701,0.000873672,0.001041956,0.002017383,0.00140022,0.009467997],"category_scores_gemma":[0.001037704,0.001062346,0.0009653069,0.0009139359,0.0007352141,0.0007833424,0.001026516,0.00349592,0.01060969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005148405,"about_ca_system_score_gemma":0.0007192269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007242306,"about_ca_topic_score_gemma":0.001293428,"domain_scores_codex":[0.9983961,0.0001707571,0.0002927388,0.0003797805,0.0006018583,0.0001586806],"domain_scores_gemma":[0.9989422,0.0001669529,0.0002249179,0.0002769047,0.0001713748,0.0002176389],"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":[0.0001469485,0.00008912392,0.0002893981,0.0002121059,0.00004293751,0.0002622757,0.00008860104,0.0002244249,0.9853743,0.001841374,0.002928908,0.008499512],"study_design_scores_gemma":[0.00009286354,0.0002402294,0.001511129,0.00007206601,0.00008004154,0.001109187,0.0000360706,0.001355021,0.8925825,0.0004939333,0.1023718,0.00005516799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2172101,0.005999098,0.6940393,0.001671858,0.001861861,0.00447098,0.03462232,0.01759433,0.02253017],"genre_scores_gemma":[0.3186017,0.0118873,0.5026855,0.001229533,0.0002658019,0.007290422,0.05759078,0.006779368,0.09366965],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009467997,"threshold_uncertainty_score":0.03167355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589447998957007,"score_gpt":0.3827329254252952,"score_spread":0.3668384454357252,"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."}}