{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001289534,0.0009084902,0.0009861741,0.0009392598,0.0005581545,0.001308451,0.001214446,0.0006647301,0.004004833],"category_scores_gemma":[0.001190793,0.0007028767,0.0006818989,0.001031896,0.0006501108,0.0007450322,0.001428059,0.003498247,0.004443671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004993508,"about_ca_system_score_gemma":0.0006310014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005872807,"about_ca_topic_score_gemma":0.001061655,"domain_scores_codex":[0.998807,0.0001776852,0.0001189674,0.0002473535,0.0005299923,0.000119043],"domain_scores_gemma":[0.9990709,0.0002553636,0.0001852191,0.0002202342,0.0001293226,0.0001389955],"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":[0.0001165996,0.00007496635,0.0002846462,0.0002548702,0.00001749761,0.0001596035,0.00007048081,0.0001958331,0.9796966,0.002327538,0.001785694,0.01501571],"study_design_scores_gemma":[0.00004600772,0.0001836946,0.001684695,0.00004552136,0.00004413487,0.001300804,0.00003796497,0.001222227,0.9284481,0.0005692957,0.06638421,0.00003333877],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.164758,0.004784726,0.7963581,0.0007439502,0.0006898884,0.002166184,0.008600453,0.006393975,0.01550472],"genre_scores_gemma":[0.345869,0.009382007,0.5522978,0.0005526778,0.0002223935,0.001733908,0.04244703,0.004245835,0.04324943],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004004833,"threshold_uncertainty_score":0.01339751,"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."}}