{"id":"W2148508291","doi":"10.1093/bfgp/elm022","title":"EUCOMM the European Conditional Mouse Mutagenesis Program","year":2007,"lang":"en","type":"article","venue":"Briefings in Functional Genomics and Proteomics","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":127,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Genetics","funders":"","keywords":"Biology; Mutagenesis; Mutant; Cre recombinase; Genetics; Gene targeting; Conditional gene knockout; Embryonic stem cell; Gene; Gene knockin; Insertional mutagenesis; Computational biology; Recombinase; Mutation; Transgene; Phenotype; Genetically modified mouse; Recombination","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003447658,0.0009548686,0.0008416019,0.002198343,0.0008466588,0.0008714615,0.002209505,0.00128431,0.03468845],"category_scores_gemma":[0.001254752,0.0004273217,0.0007537876,0.001128059,0.000391658,0.0006110758,0.00200787,0.001571042,0.02241955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008842966,"about_ca_system_score_gemma":0.00198398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002439733,"about_ca_topic_score_gemma":0.002938302,"domain_scores_codex":[0.9978995,0.0005023243,0.000120779,0.0002752269,0.000950997,0.0002512394],"domain_scores_gemma":[0.9982057,0.0001587254,0.0001862661,0.0003951693,0.0005005327,0.0005537018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001680854,0.0002431966,0.0008175471,0.0008479963,0.00008675634,0.0007224516,0.0001201146,0.001294056,0.3083339,0.04321399,0.3661087,0.2765306],"study_design_scores_gemma":[0.0001201921,0.0003160323,0.003101815,0.000116755,0.00004205678,0.001719074,0.00001661069,0.001053817,0.05623747,0.001905703,0.935323,0.00004741911],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05064706,0.02346896,0.4347621,0.008749253,0.005595577,0.002199563,0.06110127,0.02844018,0.385036],"genre_scores_gemma":[0.0988161,0.01652269,0.3562517,0.004001214,0.0006456027,0.002715148,0.127536,0.006312966,0.3871986],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03468845,"threshold_uncertainty_score":0.1160444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008958210877697763,"score_gpt":0.258466564914948,"score_spread":0.2495083540372502,"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."}}