{"id":"W3135880371","doi":"10.3390/biom11030390","title":"Targeting MMP-Regulation of Inflammation to Increase Metabolic Tolerance to COVID-19 Pathologies: A Hypothesis","year":2021,"lang":"en","type":"article","venue":"Biomolecules","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Matrix metalloproteinase; Pathogen; Inflammation; Immunology; Pneumonia; Respiratory distress; Coronavirus; Systemic inflammation; Biology; Medicine; Coronavirus disease 2019 (COVID-19); Disease; Pathology; Infectious disease (medical specialty); Internal medicine","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0007160074,0.0001492842,0.0004379232,0.0002191005,0.00009728787,0.00002041049,0.0001226302,0.00007553428,0.0001052242],"category_scores_gemma":[0.151741,0.0001315958,0.0001216695,0.0008471358,0.0001115896,0.00005299969,0.0002601551,0.00008241708,0.0000702599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00011569,"about_ca_system_score_gemma":0.0005017041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002714688,"about_ca_topic_score_gemma":0.00003386882,"domain_scores_codex":[0.9981127,0.0002060727,0.0004894871,0.0004073225,0.0004994947,0.0002849738],"domain_scores_gemma":[0.9963725,0.002223087,0.0001072045,0.0004123621,0.0004553458,0.0004295131],"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":[0.000401201,0.0001148171,0.005094494,0.0004950089,0.00007179449,0.0001032643,0.0008601943,0.001435863,0.9647349,0.0005222721,0.001162056,0.02500414],"study_design_scores_gemma":[0.002509108,0.0005847913,0.2502182,0.0004227337,0.0002255505,0.000008688061,0.0009670703,0.002128995,0.6283839,0.001424324,0.1126048,0.0005218278],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.943953,0.0006715142,0.02316738,0.03108375,0.00005980499,0.0007278435,0.00004951781,0.0001018568,0.0001853298],"genre_scores_gemma":[0.9773898,0.0002107482,0.01705278,0.004802024,0.0001495405,0.0001049324,0.00002359626,0.00001840441,0.0002481923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.336351,"threshold_uncertainty_score":0.8554043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05555588294425139,"score_gpt":0.3936960828254513,"score_spread":0.3381401998811999,"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."}}