{"id":"W3110511969","doi":"10.1128/aem.02181-20","title":"Creation of Universal Primers Targeting Nonconserved, Horizontally Mobile Genes: Lessons and Considerations","year":2020,"lang":"en","type":"article","venue":"Applied and Environmental Microbiology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computational biology; Biology; Genetics; Gene; Mobile genetic elements; Genome","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":[0.0154775,0.00124006,0.001376149,0.001053118,0.0006586754,0.002663442,0.002614354,0.002649392,0.001824468],"category_scores_gemma":[0.01476309,0.0009306117,0.0006685312,0.0005942831,0.002914543,0.0032345,0.001087909,0.004185313,0.00174262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001194467,"about_ca_system_score_gemma":0.002416471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001244392,"about_ca_topic_score_gemma":0.004459457,"domain_scores_codex":[0.9944071,0.002434181,0.0005287789,0.0006940659,0.001510644,0.0004253228],"domain_scores_gemma":[0.9867949,0.006908062,0.0008966246,0.0009683509,0.0034371,0.000995009],"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":[0.000515782,0.0006186295,0.01330177,0.004346155,0.0001186029,0.002779612,0.002035832,0.003939016,0.4652173,0.03888595,0.01400727,0.4542341],"study_design_scores_gemma":[0.0001549017,0.003643658,0.00749447,0.001907332,0.0002814119,0.01181685,0.003345046,0.01075125,0.4907732,0.07461958,0.3948962,0.0003161032],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06993908,0.09076394,0.779638,0.0427986,0.002297719,0.0007166098,0.0004051232,0.001571155,0.01186968],"genre_scores_gemma":[0.1864686,0.03560391,0.7621726,0.00566152,0.000724558,0.0008222561,0.0006319804,0.0004948393,0.007419704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0154775,"threshold_uncertainty_score":0.08185381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004715200260174419,"score_gpt":0.2156915746571245,"score_spread":0.2109763743969501,"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."}}