{"id":"W1986613969","doi":"10.1021/ac801745d","title":"High-Sensitivity NanoLC−MS/MS Analysis of Urinary Desmosine and Isodesmosine","year":2009,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Caveolin-1 and cellular processes","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institute for Research in Immunology and Cancer","funders":"National Institute on Drug Abuse; National Heart, Lung, and Blood Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Canadian Institutes of Health Research; Merck Canada; University of Utah","keywords":"Desmosine; Chemistry; COPD; Elastin; Urine; Chromatography; Liquid chromatography–mass spectrometry; Urinary system; Internal medicine; Mass spectrometry; Biochemistry; Pathology; Medicine; Amino acid","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":[0.0003179841,0.0004468437,0.0003815699,0.0008766994,0.0002946558,0.000326302,0.0002282861,0.0004370058,0.0007320703],"category_scores_gemma":[0.0005441775,0.0001158738,0.0002054339,0.0003457792,0.0002519899,0.0001283023,0.0002338117,0.0002256688,0.0003902361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001907204,"about_ca_system_score_gemma":0.0002287683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008808929,"about_ca_topic_score_gemma":0.001345393,"domain_scores_codex":[0.999688,0.0000325753,0.00002314018,0.0001125016,0.0001148227,0.00002891693],"domain_scores_gemma":[0.9998044,0.00005386363,0.000036906,0.00001438035,0.00005984012,0.0000305834],"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":[0.0002146952,0.000102015,0.01606138,0.00007420015,0.00003751931,0.000161119,0.00008336853,0.00007511427,0.9738445,0.00003303617,0.0001223816,0.009190693],"study_design_scores_gemma":[0.0000288027,0.0008877618,0.1809707,0.0000303747,0.00009511753,0.002492752,0.0001616605,0.002833565,0.8079692,0.0001487166,0.004337862,0.00004347059],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897795,0.001566062,0.006233525,0.00006108214,0.00003834968,0.00005621647,0.001352777,0.0001534255,0.0007590117],"genre_scores_gemma":[0.9741596,0.001196026,0.01927213,0.0002308226,0.00004625344,0.0001820346,0.002052911,0.00002999307,0.002830222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008808929,"threshold_uncertainty_score":0.002448976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005903756085653734,"score_gpt":0.2332546009164805,"score_spread":0.2273508448308268,"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."}}