{"id":"W2003082286","doi":"10.1371/journal.pone.0119372","title":"CRISPR MultiTargeter: A Web Tool to Find Common and Unique CRISPR Single Guide RNA Targets in a Set of Similar Sequences","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":177,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Canadian Institutes of Health Research; Genome Atlantic","keywords":"CRISPR; Cas9; Biology; Genome editing; Guide RNA; Subgenomic mRNA; Genetics; Computational biology; Gene; CRISPR interference; Genome; Genome engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002222833,0.0001435621,0.0002337867,0.00007111394,0.00001709341,0.00001328727,0.0001338782,0.0001102475,0.000007048026],"category_scores_gemma":[0.0002199649,0.0001480218,0.00002991361,0.00009148868,0.0000370432,0.000005181468,0.000124326,0.00007630088,0.000002739266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001935821,"about_ca_system_score_gemma":0.00005319166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001133767,"about_ca_topic_score_gemma":0.0002790404,"domain_scores_codex":[0.9990747,0.00004130934,0.0002628366,0.0002553164,0.0001483192,0.0002175185],"domain_scores_gemma":[0.9994798,0.00001503425,0.00004176807,0.0002487416,0.00009409754,0.0001205059],"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":[0.0000486263,0.0001812386,0.004257329,0.00006956195,0.00004576658,0.000006855095,0.00036746,0.0005472472,0.9931281,0.000004080712,0.00101661,0.0003271725],"study_design_scores_gemma":[0.0005360136,0.0005111918,0.00154518,0.00008747344,0.00002389796,0.000003001976,0.0001543291,0.001166328,0.9929249,0.00004754828,0.002793411,0.0002067189],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962113,0.001518875,0.001196348,0.0003344704,0.00003043961,0.0002544392,0.00005449275,0.00001153341,0.0003881286],"genre_scores_gemma":[0.983889,0.0001311509,0.01547719,0.0001852821,0.00006830176,0.00002371894,0.00003620684,0.0000192665,0.0001698958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01428084,"threshold_uncertainty_score":0.6036155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03865644930724763,"score_gpt":0.3001750169272018,"score_spread":0.2615185676199542,"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."}}