{"id":"W2289925386","doi":"10.1021/acs.analchem.5b04565","title":"Quantitative Detection of PEGylated Biomacromolecules in Biological Fluids by NMR","year":2016,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Biodistribution; PEG ratio; Ethylene glycol; In vivo; Proton NMR; Bovine serum albumin; Detection limit; PEGylation; Bioavailability; Drug delivery; Biophysics; Chromatography; Polyethylene glycol; Biochemistry; In vitro; Pharmacology; Stereochemistry; Organic chemistry","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":[0.0008078126,0.0005482555,0.0003070271,0.0004701506,0.0001995572,0.0003932367,0.0002644982,0.0006561358,0.000485534],"category_scores_gemma":[0.001217221,0.0001869778,0.0001479589,0.0002279042,0.0004459603,0.0004823235,0.0002931307,0.0005517156,0.0003497135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003454061,"about_ca_system_score_gemma":0.0002696639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004621912,"about_ca_topic_score_gemma":0.0005635013,"domain_scores_codex":[0.9996533,0.0001162182,0.00002123642,0.00008913631,0.0000878713,0.00003222367],"domain_scores_gemma":[0.9995366,0.0002076392,0.0001053038,0.00003209539,0.00008467841,0.00003362677],"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":[0.00002656685,0.00001049576,0.0001568307,0.00002863382,0.00000278781,0.00001297751,0.00002260946,0.0001091912,0.9973289,0.00008474743,0.00002528339,0.002191114],"study_design_scores_gemma":[0.00000433015,0.0001472313,0.001222211,0.000008449916,0.000009890585,0.00006592803,0.0000250353,0.002737971,0.9947273,0.0001408904,0.0009039193,0.000006792956],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8238609,0.003753594,0.1675922,0.0003087599,0.00006725253,0.0002221486,0.0006720617,0.0009219428,0.002601098],"genre_scores_gemma":[0.8322879,0.004596536,0.1584547,0.0003172193,0.00006919756,0.0003900456,0.000673967,0.0001094637,0.003101004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008078126,"threshold_uncertainty_score":0.004272163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02409923590980422,"score_gpt":0.3306255989283869,"score_spread":0.3065263630185827,"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."}}