{"id":"W2139753008","doi":"10.1073/pnas.0505474102","title":"Gene targeting using a promoterless gene trap vector (“targeted trapping”) is an efficient method to mutate a large fraction of genes","year":2005,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institute of Mental Health; National Heart, Lung, and Blood Institute; National Institutes of Health; Deutsche Forschungsgemeinschaft; Damon Runyon Cancer Research Foundation; University of Toronto; Howard Hughes Medical Institute","keywords":"Gene; Biology; Gene targeting; Homologous recombination; Genetics; Gene delivery; Genome; Computational biology; Transfection","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001160313,0.0001132361,0.0001600572,0.0001293933,0.0001166383,0.00001264205,0.0003704851,0.00009131925,0.000006289602],"category_scores_gemma":[0.00009822479,0.00009009177,0.00008613495,0.0004083639,0.00009389013,0.00001933125,0.00008535603,0.00007206635,1.806281e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001873693,"about_ca_system_score_gemma":0.00003376768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000697236,"about_ca_topic_score_gemma":1.104863e-7,"domain_scores_codex":[0.9986621,0.00001108544,0.000340625,0.0002992388,0.0004958796,0.0001910748],"domain_scores_gemma":[0.9994075,0.00001200434,0.0002571638,0.00001534044,0.0002558204,0.00005212384],"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":[0.00001922934,0.00006451211,0.0003120308,0.0000379175,0.00001749269,3.60916e-9,0.0003710157,0.02350588,0.9744542,0.00004892512,0.00001930831,0.0011495],"study_design_scores_gemma":[0.0001573323,0.0000825348,0.00403471,0.00002609233,0.00001541918,0.0000072837,0.00018365,0.04759587,0.9474844,0.00009515177,0.00021815,0.00009938481],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934604,0.0004464977,0.005475291,0.0003277825,0.00001591354,0.0002000693,0.00003414351,0.000005541558,0.00003438352],"genre_scores_gemma":[0.904529,0.0000154512,0.09517949,0.000108473,0.0001453662,0.000006381306,9.189136e-7,0.000007448368,0.000007482617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0897042,"threshold_uncertainty_score":0.3673835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03029263105871084,"score_gpt":0.3608025747592533,"score_spread":0.3305099437005425,"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."}}