{"id":"W2036361928","doi":"10.1002/pmic.201400627","title":"Monitoring matrix metalloproteinase activity at the epidermal–dermal interface by SILAC‐iTRAQ‐TAILS","year":2015,"lang":"en","type":"article","venue":"PROTEOMICS","topic":"Protease and Inhibitor Mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Stable isotope labeling by amino acids in cell culture; Proteases; Protease; Proteome; Extracellular matrix; Quantitative proteomics; Cell biology; Chemistry; Proteomics; Biochemistry; Metalloproteinase; Biology; Matrix metalloproteinase; Enzyme","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005465108,0.0002664138,0.0001980469,0.0000218011,0.0001838932,0.00006959551,0.0003582494,0.0002150681,0.00001546431],"category_scores_gemma":[0.0001943383,0.0002086491,0.0001320789,0.00007489727,0.00008933437,0.00002273183,0.000472847,0.000234538,0.00008077676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008879325,"about_ca_system_score_gemma":0.00010966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007241919,"about_ca_topic_score_gemma":0.000009905928,"domain_scores_codex":[0.9985116,0.0001595842,0.0002227645,0.000443835,0.0002387013,0.0004235295],"domain_scores_gemma":[0.998948,0.00001104334,0.0001502987,0.0005754514,0.0001082996,0.0002068588],"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":[0.0002410333,0.00005657407,0.0002352308,0.00001566224,0.00004843093,0.000003673002,0.00004155327,0.00005036825,0.995304,0.00001184312,0.003085308,0.0009063032],"study_design_scores_gemma":[0.0005745656,0.0002273557,0.00002386478,0.0000164222,0.00002306007,0.00003085511,0.00005124705,0.0001305389,0.9847648,0.0001851771,0.01370561,0.0002665023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839543,0.002818856,0.01080298,0.0006527015,0.0003389537,0.001011241,0.00003974739,0.00003738445,0.0003438492],"genre_scores_gemma":[0.9940355,0.00007840929,0.002399561,0.0001143993,0.0005042925,0.0002895607,0.000023029,0.00004563609,0.002509572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01062031,"threshold_uncertainty_score":0.8508462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02031993812412163,"score_gpt":0.2839066670844403,"score_spread":0.2635867289603187,"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."}}