{"id":"W2972407461","doi":"10.1007/978-1-4939-9837-1_7","title":"Generation of Large Fragment Knock-In Mouse Models by Microinjecting into 2-Cell Stage Embryos","year":2019,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"SickKids Foundation; Toronto Centre for Phenogenomics; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"Gene knockin; CRISPR; Germline; Biology; Mutant; Homologous recombination; Computational biology; Fragment (logic); Genetics; Embryo; Genome editing; Cell biology; Gene; Computer science; Algorithm","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":[0.001268929,0.001332873,0.001054133,0.001907934,0.0005999843,0.000972638,0.001574166,0.001712457,0.007491377],"category_scores_gemma":[0.0004820091,0.001050106,0.001313635,0.000535837,0.0006569996,0.0008887618,0.0007010571,0.003616225,0.003614399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006558276,"about_ca_system_score_gemma":0.0005972053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008794897,"about_ca_topic_score_gemma":0.001940704,"domain_scores_codex":[0.9992771,0.00007262237,0.0001015774,0.0002048659,0.0002254239,0.0001184656],"domain_scores_gemma":[0.9993656,0.0001201443,0.0001881851,0.00008634875,0.0000689239,0.0001707349],"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":[0.0001981777,0.0001117558,0.0002019754,0.0001083174,0.00003530338,0.0002918098,0.00007681279,0.0002494247,0.9938676,0.001745617,0.0007203274,0.002392858],"study_design_scores_gemma":[0.0001472943,0.0003158523,0.001654792,0.00005788953,0.0001462546,0.0008017716,0.00005495897,0.00256155,0.9668277,0.0004673532,0.02693384,0.00003073109],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6328037,0.006214033,0.3103247,0.001589624,0.001899156,0.002853755,0.022959,0.006253495,0.0151025],"genre_scores_gemma":[0.7038478,0.008213279,0.1636836,0.000945769,0.0002342912,0.004806384,0.01930309,0.002303365,0.09666244],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.007491377,"threshold_uncertainty_score":0.02506119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01542819235872232,"score_gpt":0.3877765318037495,"score_spread":0.3723483394450272,"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."}}