{"id":"W4387880240","doi":"10.1021/acssuschemeng.3c05735","title":"CRISPR Tools in Bacterial Whole-Cell Biocatalysis","year":2023,"lang":"en","type":"article","venue":"ACS Sustainable Chemistry & Engineering","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Agencia Nacional de Investigación e Innovación; Programa de Desarrollo de las Ciencias Básicas","keywords":"CRISPR; Biochemical engineering; Biocatalysis; Biotechnology; Metabolic engineering; Synthetic biology; Industrial biotechnology; Nanotechnology; Computational biology; Biology; Engineering; Materials science; Genetics; Catalysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008841273,0.000639939,0.0006405154,0.0008009082,0.0003135683,0.001218032,0.0007908635,0.0009879958,0.001469328],"category_scores_gemma":[0.0007934444,0.0004850289,0.0005571868,0.0004847347,0.000550919,0.0005445843,0.0008211182,0.001454657,0.001485427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006354162,"about_ca_system_score_gemma":0.0004655784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005969447,"about_ca_topic_score_gemma":0.001295234,"domain_scores_codex":[0.9992237,0.0001976036,0.00009701908,0.0001216004,0.0002858672,0.00007428942],"domain_scores_gemma":[0.9996508,0.0001756352,0.00005081495,0.00005667207,0.00003506758,0.00003108751],"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":[0.0001322293,0.00007077233,0.0003606545,0.0006481474,0.00005283423,0.00050387,0.0001148891,0.003605714,0.9304836,0.01020359,0.00187413,0.05194956],"study_design_scores_gemma":[0.00003210048,0.0002509367,0.0009036633,0.0001576636,0.00005601595,0.001017263,0.00006122211,0.007875117,0.9036609,0.003585809,0.08232786,0.00007141056],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.2518119,0.03730637,0.6592414,0.004117806,0.001290081,0.0005067376,0.00527556,0.01439533,0.02605481],"genre_scores_gemma":[0.5598188,0.03095923,0.3913988,0.0008956544,0.0001234817,0.000401118,0.003338673,0.0007363118,0.0123279],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.001469328,"threshold_uncertainty_score":0.004915357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00563463064542693,"score_gpt":0.2470328646731971,"score_spread":0.2413982340277701,"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."}}