{"id":"W4400876617","doi":"10.1021/acssynbio.4c00377","title":"Culture Wars: Empirically Determining the Best Approach for Plasmid Library Amplification","year":2024,"lang":"en","type":"letter","venue":"ACS Synthetic Biology","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Stem Cell Network","keywords":"Library; Plasmid; Genomic library; Biology; Computational biology; Sequence (biology); Outlier; Computer science; Insert (composites); Genetics; DNA; Gene; Base sequence; Artificial intelligence; 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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0001675521,0.0004521114,0.0003468205,0.0000725112,0.0002038778,0.00007725105,0.0009986692,0.002391898,0.00001439829],"category_scores_gemma":[0.00009553928,0.000298918,0.0003076805,0.0001193534,0.0004479883,0.000003336925,0.0003563091,0.0008675811,0.00003797278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001441585,"about_ca_system_score_gemma":0.0001138868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002941383,"about_ca_topic_score_gemma":6.717607e-7,"domain_scores_codex":[0.9977511,0.0001701168,0.0004107888,0.001102642,0.00007752893,0.0004878686],"domain_scores_gemma":[0.9985234,0.00008546539,0.0002082418,0.001050109,0.00008621091,0.00004661574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001554923,0.00004864285,0.00006778877,0.00009284041,0.0001473943,0.000001725442,0.00002124956,0.000001138884,0.02815254,0.0007232281,0.9672315,0.003496456],"study_design_scores_gemma":[0.000117089,0.0003461752,0.000004647487,0.00002520697,0.0001569092,0.00004673508,0.00001595698,0.00004985106,0.01666681,0.001771475,0.9804155,0.0003836931],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.003374076,0.007271228,0.1817475,0.783984,0.0009606198,0.005458649,0.00369652,0.0004522674,0.01305514],"genre_scores_gemma":[0.02742768,0.002316808,0.04571743,0.8240627,0.008036821,0.007058085,0.07095286,0.0004630924,0.01396452],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1360301,"threshold_uncertainty_score":0.9999463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02326250431577864,"score_gpt":0.2876617163626948,"score_spread":0.2643992120469161,"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."}}