{"id":"W2321973970","doi":"10.1021/tx5002095","title":"Covalent Binding of 4-Hydroxynonenal to Matrix Metalloproteinase 13 Studied by Liquid Chromatography–Mass Spectrometry","year":2014,"lang":"en","type":"article","venue":"Chemical Research in Toxicology","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Hôpital du Sacré-Cœur de Montréal; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Tandem mass spectrometry; Matrix metalloproteinase; 4-Hydroxynonenal; Mass spectrometry; Collagenase; Lipid peroxidation; Selected reaction monitoring; Chromatography; Cysteine; Biochemistry; Covalent bond; Oxidative stress; Enzyme; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001477075,0.0002020787,0.0006940963,0.000836827,0.00005577074,0.00001092808,0.0002393132,0.0002583624,0.0002732142],"category_scores_gemma":[0.0008813372,0.0001804284,0.0001443175,0.00120455,0.0002924826,0.00004153787,0.0002125386,0.000571355,0.0001082645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002768112,"about_ca_system_score_gemma":0.0001049451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002182468,"about_ca_topic_score_gemma":0.000009044216,"domain_scores_codex":[0.9971397,0.0002348546,0.0004524255,0.000527365,0.0007258629,0.0009198212],"domain_scores_gemma":[0.9984662,0.0004620682,0.00006280112,0.0003860109,0.0001427839,0.0004801677],"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":[0.001134916,0.0007094414,0.0004450681,0.0001388963,0.00006495077,0.0001506158,0.00005327519,3.663577e-7,0.9946213,0.0009586251,0.0005928012,0.001129737],"study_design_scores_gemma":[0.00378702,0.009587609,0.00005994055,0.0001705497,0.00002844035,0.00003891266,0.00009426729,0.00001869656,0.9840941,0.0005149948,0.001465906,0.0001394934],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994272,0.0005732288,0.000116764,0.001478072,0.00007932029,0.001123539,0.00001767684,0.00003806698,0.002301353],"genre_scores_gemma":[0.9954446,0.00007588014,0.003554908,0.00008678947,0.000103621,0.0002776862,0.00003795418,0.00003196478,0.0003866166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01052714,"threshold_uncertainty_score":0.7357656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04061117996121175,"score_gpt":0.3725369053445601,"score_spread":0.3319257253833483,"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."}}