{"id":"W2098880867","doi":"10.1534/g3.114.010868","title":"The Insertion Green Monster (iGM) Method for Expression of Multiple Exogenous Genes in Yeast","year":2014,"lang":"en","type":"article","venue":"G3 Genes Genomes Genetics","topic":"Redox biology and oxidative stress","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"National Institute of General Medical Sciences; Canada Excellence Research Chairs, Government of Canada; National Human Genome Research Institute; National Institute on Aging; Defense Advanced Research Projects Agency; Advanced Research Projects Agency; National Institutes of Health; Canadian Institute for Advanced Research; Ellison Medical Foundation; Avon Foundation for Women; Krembil Foundation; U.S. Department of Energy","keywords":"Gene; Biology; Yeast; Saccharomyces cerevisiae; Genetics; Selenoprotein; Heterologous expression; Genome; Computational biology; Methionine sulfoxide; Methionine; Recombinant DNA; Biochemistry; Enzyme","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009838439,0.001058554,0.0007017383,0.001118717,0.0005946029,0.0005501056,0.0009050143,0.0005916813,0.001577346],"category_scores_gemma":[0.0002805358,0.0005108013,0.0008085939,0.000654642,0.0005478285,0.0003931235,0.001279585,0.002071146,0.001280044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004370197,"about_ca_system_score_gemma":0.0005491886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006595087,"about_ca_topic_score_gemma":0.001196422,"domain_scores_codex":[0.9994162,0.0001243138,0.00005470783,0.0001061449,0.0002257618,0.00007292065],"domain_scores_gemma":[0.9998494,0.00003464513,0.0000281454,0.00004457802,0.00001518866,0.00002801205],"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":[0.0001231124,0.00004142017,0.0001329078,0.0001416419,0.00001752777,0.0001237598,0.00006850068,0.0001312048,0.9827573,0.002096398,0.0004870141,0.01387915],"study_design_scores_gemma":[0.00002941024,0.00016854,0.0005182532,0.00001725822,0.00003359306,0.0005578792,0.0000208511,0.0006867936,0.9638394,0.0002585362,0.0338469,0.00002267646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1701625,0.0062008,0.8062457,0.0007723061,0.000669551,0.001301413,0.001572364,0.004564742,0.008510682],"genre_scores_gemma":[0.3875409,0.00937747,0.5696849,0.0004727896,0.00009671406,0.001352503,0.00441817,0.001012094,0.02604443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001577346,"threshold_uncertainty_score":0.00527674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01602476358123056,"score_gpt":0.2764225771229233,"score_spread":0.2603978135416927,"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."}}