Is dietary fat associated with the risk of age-related macular degeneration? Protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
Previous studies evaluating the association of dietary fat and risk of age-related macular degeneration (AMD) yield discrepant results. The objective of this systematic review (SR) and meta-analysis is to establish whether an association exists between dietary fat and AMD. This protocol was developed in line with the quality requirements of the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) statement. PubMed and EMBASE will be searched for randomized controlled trials (RCTs), non-randomized trials (NRTs), cross-sectional studies, cohort studies, and case-control studies that evaluate the total incidence of AMD. The data extraction content and quantitative analysis will be carried out systematically. Newcastle-Ottawa Scale (NOS), the Cochrane risk of bias tool, and quality assessment tools will be used for quality assessment. This SR will synthesize evidence to determine if there is an association between dietary fat and AMD. The evidence would provide rationale for future research and serve as a basis for the development of future guidelines. Results are expected to be publicly available in mid 2020.PROSPERO registration number: CRD42019137086.
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 | 0.064 | 0.116 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.022 | 0.027 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.071 | 0.008 |
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".