{"id":"W4220695330","doi":"10.1101/2022.03.14.484339","title":"Genetic engineering of <i>Acidithiobacillus ferridurans</i> with CRISPR-Cas9/dCas9 systems","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Cas9; CRISPR; Gene; Acidithiobacillus ferrooxidans; Subgenomic mRNA; Biology; Genome editing; Guide RNA; Computational biology; Acidithiobacillus; Synthetic biology; Genetics; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005063763,0.000789863,0.0009155195,0.0004365907,0.0001322488,0.0001727442,0.0006380433,0.0004225693,0.0001275734],"category_scores_gemma":[0.00005877917,0.0008045716,0.0002134069,0.0005823408,0.00005577292,0.0001510885,0.0002539173,0.001588119,0.00002530129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003765891,"about_ca_system_score_gemma":0.0001950025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009751687,"about_ca_topic_score_gemma":0.000002122814,"domain_scores_codex":[0.9969538,0.0001097411,0.0008628634,0.0007581523,0.0006818319,0.0006335814],"domain_scores_gemma":[0.9978511,0.00006856687,0.000320366,0.00125296,0.0002158719,0.0002910822],"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":[0.00002907125,0.00007123664,0.001115152,0.002886748,0.0004730331,0.0001466018,0.00002361421,0.3539313,0.640931,0.00019448,0.0001936607,0.000004133668],"study_design_scores_gemma":[0.003019782,0.0004856102,0.07491603,0.003775992,0.001352095,0.00000260463,0.00009928254,0.2868547,0.5070654,8.328893e-7,0.1149298,0.007497856],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9526372,0.007327316,0.03089228,0.00002010133,0.005583834,0.001157,0.0005179878,0.001738869,0.0001254018],"genre_scores_gemma":[0.9934807,0.0004731198,0.005036906,0.00002548927,0.0004086192,0.0002780232,7.93106e-7,0.0002880718,0.000008233187],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1338657,"threshold_uncertainty_score":0.9994405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009280582321676646,"score_gpt":0.1840885146828518,"score_spread":0.1748079323611752,"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."}}