{"id":"W4389569968","doi":"10.1101/2023.12.10.570953","title":"Highly efficient transgenic mouse production using piggyBac and its application to rapid phenotyping at the founder generation","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Japan Society for the Promotion of Science; Kanazawa University; Kindai University","keywords":"Transgene; Microinjection; Biology; Transposable element; Genetically modified mouse; Phenotype; First generation; Fourth generation; Genetics; Genetically modified organism; Genome; Computational biology; Cell biology; Gene; Third generation; Computer science; Population; Medicine","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":[0.001731217,0.0009165131,0.0006289384,0.001298227,0.0003174728,0.0006100665,0.0006164594,0.0007724834,0.002008106],"category_scores_gemma":[0.0006388391,0.0004320967,0.0006056975,0.0004742178,0.0005436282,0.0004108282,0.0008893018,0.001285032,0.001596017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002771121,"about_ca_system_score_gemma":0.0002997743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004447052,"about_ca_topic_score_gemma":0.0004213216,"domain_scores_codex":[0.999244,0.0001781246,0.000101094,0.0002002224,0.0001830451,0.00009342541],"domain_scores_gemma":[0.9994457,0.0001747216,0.0001215404,0.0001199137,0.00006284624,0.0000753541],"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":[0.00001795672,0.00000873607,0.00007023603,0.00002094016,0.000003610726,0.00004931591,0.00001329259,0.00005610717,0.9978758,0.0001526223,0.00006312355,0.001668295],"study_design_scores_gemma":[0.00001069902,0.00009946187,0.001357382,0.00001144338,0.00002166301,0.0003794011,0.000007644847,0.0008353645,0.9909662,0.0001444979,0.006152843,0.00001344296],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3240615,0.002070604,0.6614461,0.0004369257,0.000252365,0.0007762476,0.002369169,0.0039401,0.004647051],"genre_scores_gemma":[0.5550442,0.003346688,0.4175513,0.0003637845,0.0000855675,0.0009653337,0.005982451,0.001963268,0.01469745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002008106,"threshold_uncertainty_score":0.009155631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02058368063948912,"score_gpt":0.2598149044445046,"score_spread":0.2392312238050155,"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."}}