The association of serum vascular endothelial growth factor levels and psoriasis vulgaris
Bibliographic record
Abstract
BACKGROUND: In recent years, more and more attention has been paid to the role of skin microcirculation in the pathogenesis of psoriasis. The vascular network of the skin is mainly distributed in the dermis and the subcutaneous fat layer join. The microvessels are composed of terminal arterioles, arteriovenous capillaries, and postcapillary venules. Vascular endothelial growth factor (VEGF) plays an important role in the pathogenesis of psoriasis by promoting angiogenesis. The purpose of this study is to evaluate the relationship between serum VEGF and psoriasis vulgaris. METHODS: Embase, CENTRAL, PubMed, China Biology Medicine Database, China National Knowledge Database, Wan Fang Database, and Chong Qing VIP Database will be searched to collect case-control studies and cohort studies and evaluate the relationship between serum VEGF and psoriasis vulgaris. The search time limits will be from the establishment of the database to December 2020. Two researchers will independently screen the studies, extract data, and evaluate the risk of bias of the studies. The Meta-analysis will be carried out with the RevMan5.3 software. The quality of all included studies will be evaluated by the Newcastle-Ottawa scale. RESULTS: This study will evaluate the relationship between serum VEGF and the pathogenesis of psoriasis vulgaris. CONCLUSION: This study will provide a theoretical basis for the pathogenesis of psoriasis vulgaris. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/6DV8P.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".