{"id":"W2944298841","doi":"10.1002/yea.3400","title":"Integrating after CEN Excision (ICE) Plasmids: Combining the ease of yeast recombination cloning with the stability of genomic integration","year":2019,"lang":"en","type":"article","venue":"Yeast","topic":"Fungal and yeast genetics research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of General Medical Sciences; National Institutes of Health; Computer Modelling Group","keywords":"Plasmid; Biology; Cloning (programming); Cloning vector; Multiple cloning site; Genetics; Subcloning; Yeast; Computational biology; FLP-FRT recombination; Molecular cloning; Recombination; Vector (molecular biology); Gene; Recombinant DNA; Genetic recombination; Computer science; Complementary DNA","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":[0.0004917662,0.0001057314,0.000117818,0.00002971774,0.00005682553,0.00002207417,0.0002313174,0.0000649507,0.00006288169],"category_scores_gemma":[0.00007057588,0.00005708627,0.00005914102,0.0001041501,0.0001282275,0.000006699711,0.0001336199,0.0001536417,0.00001042582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001687943,"about_ca_system_score_gemma":0.00008097981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006118917,"about_ca_topic_score_gemma":0.0001361642,"domain_scores_codex":[0.9990799,0.0001391412,0.0002088559,0.000207771,0.0002202723,0.0001440897],"domain_scores_gemma":[0.9992163,0.00003939887,0.0001366123,0.0003652734,0.0002122544,0.00003018611],"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":[0.0003982426,0.00005137825,0.01365315,0.00003170383,0.00002333029,2.237642e-7,0.0006943849,0.00009343456,0.9815224,0.00009542275,0.00004254783,0.003393797],"study_design_scores_gemma":[0.0007609644,0.0007660664,0.07431626,0.0001275973,0.00002094932,0.000005895306,0.003692251,0.002752427,0.916776,0.00006928666,0.0005600599,0.0001522611],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977389,0.0001610985,0.0005952186,0.0001457824,0.00007086024,0.0003086445,0.0000252272,0.0000033613,0.0009509349],"genre_scores_gemma":[0.9994139,0.0000155904,0.0002636066,0.00002734065,0.00003944791,0.0000200683,0.00004484997,0.00001399033,0.0001611701],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06474639,"threshold_uncertainty_score":0.2327911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01089537680939214,"score_gpt":0.2404217173178915,"score_spread":0.2295263405084993,"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."}}