Predictive factors for lymph node metastasis in early gastric cancer with signet ring cell histology: a meta‐analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Less invasive surgery is widely used in the treatment of early gastric cancer; however, no definite guidelines exist regarding indications for less invasive surgery to treat early gastric cancer with signet ring cell histology. The aim of this study was to identify risk factors for lymph node metastasis (LNM) in early signet ring cell carcinoma (SRC). An extensive search of PubMed, Embase and the Cochrane library was performed for pertinent articles involving early SRC and LNM. METHODS: Eligible data (gender, depth of invasion, lymphovascular invasion, size, ulceration, macroscopic type and location) were extracted from the included studies and systematically reviewed via a meta-analysis. Review Manager version 5.3 was used to perform the data processing. The Newcastle-Ottawa Scale was utilized to evaluate the quality of the included articles. RESULTS: Fourteen studies were included in the final analysis. After meta-analysis, female gender, submucosal invasion, lymphovascular invasion and size >20 mm were associated with LNM in early SRC. CONCLUSION: Four variables were identified as risk factors for LNM in early SRC. The significance of the results of the present study should be further confirmed in more early SRC patients for future clinical use.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it