{"id":"W2897377957","doi":"10.1002/dta.2518","title":"Analysis of insulin and insulin analogs from dried blood spots by means of liquid chromatography–high resolution mass spectrometry","year":2018,"lang":"en","type":"article","venue":"Drug Testing and Analysis","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"Insulin aspart; Chromatography; Chemistry; Mass spectrometry; Insulin; Analyte; Liquid chromatography–mass spectrometry; Insulin analog; Ion suppression in liquid chromatography–mass spectrometry; Quantitative analysis (chemistry); Internal medicine; Human insulin; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009950352,0.0010638,0.0007079149,0.00157605,0.0003806148,0.0007552519,0.0006588949,0.0008638379,0.001192032],"category_scores_gemma":[0.001481584,0.0002922656,0.0005730399,0.0009884899,0.0004978029,0.0004090198,0.0004958277,0.001000794,0.001068522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002359429,"about_ca_system_score_gemma":0.000601944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005403437,"about_ca_topic_score_gemma":0.0008082931,"domain_scores_codex":[0.9980922,0.0003690355,0.0001289286,0.0004405838,0.0008862632,0.00008282061],"domain_scores_gemma":[0.9994572,0.000137939,0.0001284893,0.00006140797,0.0001741027,0.00004097232],"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":[0.0002326106,0.0001050681,0.0006928701,0.0001968363,0.0000739578,0.0002472535,0.00005597965,0.0001170716,0.9785939,0.0002054755,0.000251788,0.01922704],"study_design_scores_gemma":[0.00005659329,0.0008629097,0.007852071,0.00005102529,0.0001337951,0.002155627,0.00009410154,0.004334214,0.9770858,0.0003604038,0.006950614,0.00006273716],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5324768,0.0258573,0.4158569,0.0007638448,0.0007254958,0.001766872,0.003756176,0.003505377,0.01529125],"genre_scores_gemma":[0.5755741,0.01940213,0.3879148,0.001530248,0.0003488638,0.001426156,0.003580882,0.0002547809,0.009968081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00157605,"threshold_uncertainty_score":0.005262315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0129783701892968,"score_gpt":0.2494783571457034,"score_spread":0.2364999869564066,"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."}}