{"id":"W2900039373","doi":"10.20944/preprints201811.0159.v1","title":"A Multiplex CRISPR/Cas9 System for Use as an Anti-BmNPV Therapeutic","year":2018,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"CRISPR; Cas9; Genome editing; Biology; Subgenomic mRNA; Multiplex; Computational biology; Genome engineering; Gene; Transcription activator-like effector nuclease; Genome; Genetics","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":[0.000338521,0.0006224844,0.0005685379,0.0004810537,0.0003276514,0.0006983199,0.0005070691,0.0007382192,0.002020717],"category_scores_gemma":[0.0001705177,0.0003508361,0.0004255017,0.0002444098,0.0002305832,0.0004417156,0.0005029498,0.0008603836,0.001040503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005078897,"about_ca_system_score_gemma":0.0003459954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007799813,"about_ca_topic_score_gemma":0.001037916,"domain_scores_codex":[0.9994801,0.00003406733,0.00004916378,0.0001855064,0.0002060376,0.0000451367],"domain_scores_gemma":[0.999912,0.00000851693,0.00002423343,0.00001851373,0.00001407516,0.00002266771],"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":[0.00004684235,0.00002094132,0.00008890303,0.00005245624,0.00001129177,0.00005906177,0.00001013824,0.0001285789,0.9915667,0.0003680459,0.0003037922,0.007343179],"study_design_scores_gemma":[0.00001301153,0.000132176,0.0004934319,0.000005486203,0.00002737358,0.0004367568,0.000005184676,0.002238955,0.9813576,0.00008877205,0.01518594,0.00001527844],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4993517,0.008298176,0.4588879,0.0007608047,0.0007826526,0.001265419,0.0052718,0.008624567,0.0167569],"genre_scores_gemma":[0.7507097,0.003099357,0.2134892,0.0002851904,0.00006924089,0.0006876522,0.005229689,0.0002866566,0.02614327],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002020717,"threshold_uncertainty_score":0.006759942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09654238614321489,"score_gpt":0.3948646923677713,"score_spread":0.2983223062245565,"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."}}