{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02406229,0.001498133,0.00207384,0.001726094,0.001706074,0.003887325,0.002241144,0.004670375,0.002591914],"category_scores_gemma":[0.0835691,0.001598621,0.001098612,0.002125251,0.002820289,0.003969818,0.002502004,0.004637523,0.003874068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003025935,"about_ca_system_score_gemma":0.001834866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001353492,"about_ca_topic_score_gemma":0.003506295,"domain_scores_codex":[0.9807767,0.008309054,0.001588572,0.002336274,0.006373738,0.0006155946],"domain_scores_gemma":[0.9260184,0.05670574,0.003795952,0.004744262,0.007758738,0.0009768727],"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":[0.002014659,0.0009268432,0.0189009,0.002560446,0.0003074662,0.0009964851,0.0009096284,0.009435166,0.7092695,0.009660803,0.01489267,0.2301254],"study_design_scores_gemma":[0.0001694764,0.00313636,0.01069971,0.0005088082,0.0003251352,0.002425002,0.0006538123,0.04475431,0.872731,0.01272582,0.05159051,0.0002799971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2842304,0.03667598,0.6189235,0.02698095,0.00333035,0.002836243,0.001555242,0.003162373,0.02230503],"genre_scores_gemma":[0.3778365,0.01457769,0.5750591,0.01593931,0.0009233168,0.004244939,0.002315968,0.001315486,0.007787712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02406229,"threshold_uncertainty_score":0.1272551,"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."}}