{"id":"W4317781165","doi":"10.1007/978-1-0716-2982-6_16","title":"Interrogation of Functional miRNA-Target Interactions by CRISPR/Cas9 Genome Engineering","year":2023,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Biotechnology and Biological Sciences Research Council; Wellcome Trust","keywords":"CRISPR; Biology; Computational biology; microRNA; Cas9; Gene silencing; Guide RNA; Genome; Genetics; Genome engineering; Gene","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":[0.001002181,0.0006568225,0.0006962934,0.0004233741,0.0005326627,0.001309015,0.0007394049,0.0007934403,0.002103249],"category_scores_gemma":[0.001139458,0.0004655393,0.0006762152,0.0002791385,0.0006062721,0.0005607564,0.0005933091,0.001563975,0.001523794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007764905,"about_ca_system_score_gemma":0.0004450455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005376124,"about_ca_topic_score_gemma":0.001026856,"domain_scores_codex":[0.9987267,0.0001555525,0.0001312406,0.0002887514,0.0005370087,0.0001608481],"domain_scores_gemma":[0.9993705,0.0002290105,0.0001483013,0.00009982806,0.00008570205,0.00006673577],"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":[0.00004580429,0.00001526299,0.0001022765,0.00003172065,0.000006988127,0.00003394041,0.00001111528,0.0001311428,0.9983505,0.0003151767,0.00004881168,0.0009072424],"study_design_scores_gemma":[0.000004942497,0.00003120039,0.0005682175,0.000002688796,0.000007322253,0.00009834633,0.00001177482,0.002010775,0.9956912,0.000126405,0.001440698,0.000006348575],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8348701,0.002446364,0.1493399,0.000520872,0.0002657516,0.000197378,0.001807938,0.001447746,0.009103964],"genre_scores_gemma":[0.9577577,0.0006842422,0.03565735,0.0002069019,0.00001490915,0.0001137059,0.001279033,0.0002897279,0.003996354],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002103249,"threshold_uncertainty_score":0.00703603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01558901085078869,"score_gpt":0.4095819477102664,"score_spread":0.3939929368594777,"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."}}