Association of vitamin D receptor gene polymorphism with type 1 diabetes mellitus risk in children
Bibliographic record
Abstract
BACKGROUND: Recent genetic association studies showed that there are contradictory results on the relationship between vitamin D receptor (VDR) gene polymorphisms and type 1 diabetes mellitus (T1DM) risk in children. The purpose of this systematic review is to collect the currently available evidence to evaluate the relationship between VDR gene polymorphisms and the risk of T1DM in children. METHODS: Such medical databases as Wanfang Data, Chinese Biomedical Literature Database, Chinese National Knowledge Infrastructure, Chongqing VIP Chinese Science and Technology Periodical Database, PubMed, Embase, and Web of Science were extensively searched for relevant literatures published before June 2021 with the focus on the relationship between VDR gene polymorphisms and the risk of T1DM in children. The risk of bias was evaluated as per the Newcastle-Ottawa Scale by 2 independent researchers. Meta-analysis was performed to quantify the relationship between VDR gene polymorphisms and T1DM risk in children. RESULTS: The results of this meta-analysis would be submitted to a peer-reviewed journal for publication. CONCLUSION: The relationship between VDR gene polymorphisms and T1DM risk in children is explored via this meta-analysis. ETHICS AND DISSEMINATION: Ethical approval was not required for this study. The systematic review will be published in a peer-reviewed journal, presented at conferences, and shared on social media platforms. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/Q8XA5.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".