Long-term Cardiovascular Mortality in Patients with Gastrectomy: A meta-analysis
Bibliographic record
Abstract
Supplementary Materials: The following are available online at www.mdpi.com/xxx/s1. Figure S1: Funnel plot with trim and fill. (a) Coronary heart disease and (b) stroke. The closed dots indicate observed studies and the open dots indicate the missing studies imputed with the trim and fill method. The dashed lines that create a triangular area indicate the 95% confidence interval and the vertical dashed line represent the overall effect size, Figure S2: Forest plots of meta-analysis according to smoking status in enrolled studies. (a) Coronary heart disease (b) Stroke, Figure S3: Forest plots of meta-analysis of studies enrolled. (a) All-cause mortality and (b) Lung cancer, Figure S4: Forest plots of meta-analysis according to disease type. (a) Coronary heart disease (b) Stroke, Table S1: PRISMA check list, Table S2: PICOS table for study question, Table S3: Newcastle-Ottawa quality assessment scale, Table S4: Smoking status of patients from studies in Table 1.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.046 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".