{"id":"W3047430625","doi":"10.1016/j.omtm.2020.08.005","title":"Rapid In-Process Monitoring of Lentiviral Vector Particles by High-Performance Liquid Chromatography","year":2020,"lang":"en","type":"article","venue":"Molecular Therapy — Methods & Clinical Development","topic":"Viral Infectious Diseases and Gene Expression in Insects","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; National Research Council Canada","funders":"Canada Research Chairs","keywords":"Chromatography; Process (computing); Viral vector; Chemistry; Materials science; Computer science; Biochemistry; Recombinant DNA","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":[0.0007233933,0.0002535874,0.0003974811,0.00004463658,0.00006805382,0.00001950435,0.0003095232,0.0001910983,0.00003038032],"category_scores_gemma":[0.000162214,0.0002303913,0.0001953713,0.0002814546,0.0001113874,0.00001010092,0.0001157054,0.0001788403,0.00000560843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009689098,"about_ca_system_score_gemma":0.0001260696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005037074,"about_ca_topic_score_gemma":2.32167e-7,"domain_scores_codex":[0.9975037,0.0005270204,0.0008421372,0.0005659338,0.0002315042,0.0003296927],"domain_scores_gemma":[0.9991435,0.00004583198,0.0002292151,0.0002891709,0.00008951062,0.0002028068],"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":[0.0007874891,0.0003055002,0.03293239,0.00005028931,0.0001683572,0.00000408943,0.0001298349,0.00007345167,0.8733919,0.00000560209,0.000116804,0.09203432],"study_design_scores_gemma":[0.001267727,0.001263543,0.02493861,0.00004940345,0.000009976289,6.796261e-7,0.00003221763,0.00003453834,0.9654885,0.00003786429,0.006595524,0.000281399],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851222,0.00400083,0.01010833,0.0001306216,0.0003084344,0.000250711,0.000005490252,0.00002605686,0.00004732012],"genre_scores_gemma":[0.9611784,0.00211309,0.03576965,0.0006687387,0.0001148163,0.00008427966,0.00002675376,0.00003721986,0.000007037524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09209663,"threshold_uncertainty_score":0.9395086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04810620249247679,"score_gpt":0.381543067408778,"score_spread":0.3334368649163012,"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."}}