{"id":"W4385691312","doi":"10.1021/acs.est.3c02492","title":"Genetic Engineering of <i>Acidithiobacillus ferridurans</i> Using CRISPR Systems To Mitigate Toxic Release in Biomining","year":2023,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Waterloo","funders":"Hospital for Sick Children; University of Toronto","keywords":"CRISPR; Acidithiobacillus; Cas9; Chemistry; Acidithiobacillus ferrooxidans; Computational biology; Gene; Materials science; Biology; Bioleaching; Metallurgy; Biochemistry","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":[0.000230994,0.0007357509,0.0003883311,0.0002847049,0.0002325263,0.0004186933,0.0005242212,0.0004047093,0.0007440218],"category_scores_gemma":[0.0002402011,0.0002065172,0.0005087997,0.0002707005,0.000267618,0.0002125648,0.0004492713,0.0006149269,0.0003315184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004291688,"about_ca_system_score_gemma":0.0003707066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002304573,"about_ca_topic_score_gemma":0.002894237,"domain_scores_codex":[0.9997515,0.00002811614,0.00003537826,0.00005354234,0.00008737201,0.00004408352],"domain_scores_gemma":[0.9998478,0.00001974098,0.00006211677,0.00002119769,0.0000194262,0.0000297983],"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":[0.00002030676,0.00001775679,0.0001325502,0.0000370852,0.000006374273,0.0000591981,0.00001474252,0.0002276587,0.9975902,0.0001821139,0.000045918,0.001665983],"study_design_scores_gemma":[0.000008453621,0.00009747022,0.001366549,0.000008355389,0.00001769446,0.0002174439,0.00003019072,0.001635518,0.9920309,0.00007100401,0.004504764,0.00001170528],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9547408,0.0006395918,0.03915804,0.0002496953,0.00007941329,0.0001525767,0.0009877463,0.0008419215,0.003150138],"genre_scores_gemma":[0.9684096,0.0004676881,0.02574451,0.00007950405,0.00001038132,0.0000910984,0.001125372,0.00015167,0.00392011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002304573,"threshold_uncertainty_score":0.004582286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006056774478126588,"score_gpt":0.2496458378345705,"score_spread":0.243589063356444,"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."}}