{"id":"W2094666260","doi":"10.1038/npre.2012.6876.1","title":"A quantitative model for efficient construction of lentiviral vectors with a unique clone site","year":2012,"lang":"en","type":"preprint","venue":"Nature Precedings","topic":"Virus-based gene therapy research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Insert (composites); Cloning (programming); Computational biology; clone (Java method); Mutagenesis; Biology; Transgene; Viral vector; Mutant; Recombinant DNA; Molecular biology; Gene; Genetics; Computer science; 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":[0.001892357,0.0009807041,0.0008324228,0.00117001,0.0003400811,0.001160159,0.001605308,0.000933168,0.001298659],"category_scores_gemma":[0.002288757,0.0008195568,0.0008240616,0.000697009,0.0008601238,0.001053159,0.0006833555,0.001803984,0.001077151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001651288,"about_ca_system_score_gemma":0.0006887561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009723188,"about_ca_topic_score_gemma":0.0005114156,"domain_scores_codex":[0.9982592,0.000378443,0.0001115796,0.0004252132,0.0007033942,0.0001220797],"domain_scores_gemma":[0.9990479,0.0004421691,0.0001811246,0.0001331296,0.0001485074,0.0000471547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001069203,0.0001373653,0.0006425088,0.0001816926,0.00004102504,0.00010919,0.00007485212,0.01712552,0.9371779,0.02936848,0.0004586993,0.01457591],"study_design_scores_gemma":[0.00004943127,0.0004648838,0.0007204732,0.00002794566,0.0000666975,0.000451382,0.00002358903,0.3517564,0.6243433,0.01123852,0.01079273,0.00006461665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05042577,0.0005244314,0.9464101,0.000103535,0.00005319896,0.0001858883,0.0002927146,0.0007106581,0.001293643],"genre_scores_gemma":[0.4152746,0.0009180622,0.5756278,0.0001628139,0.00004555596,0.001242726,0.001118636,0.0005193159,0.005090389],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001892357,"threshold_uncertainty_score":0.01198101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01995800019339663,"score_gpt":0.3228978274428463,"score_spread":0.3029398272494497,"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."}}