Bibliographic record
Abstract
BACKGROUND: Lymph node status is an important prognostic factor in the staging of colorectal carcinoma. Several adjunctive solutions have been used to increase the yield of pericolic lymph nodes from colorectal cancer resection specimens. METHODS: During 1998 at the Grey Bruce Regional Health Centre (Owen Sound, Ontario), 67 colonic resections were performed for colorectal cancer. Lymph nodes were identified using GEWF solution (glacial acetic acid, ethanol, distilled water, and formaldehyde) in 35 cases, and by the conventional method of sectioning, inspection, and palpation in 32 cases. RESULTS: There were no significant differences between GEWF and non-GEWF cases with respect to patient age, length of resection, size of tumor, tumor histologic type, tumor differentiation, or depth of tumor penetration into the bowel wall. Use of GEWF led to a significant increase in the number of lymph nodes found (10.2 +/- 4.9 per case) compared with non-GEWF cases (6.8 +/- 3.9 per case) (P =.002). In GEWF cases 358 lymph nodes were identified, 82 with metastases, whereas in the non-GEWF cases 218 lymph nodes were found, 41 with metastases. The size of positive lymph nodes in the GEWF group (0.5 +/- 0.2 cm) was significantly smaller than in the non-GEWF group (0.7 +/- 0.4 cm) (P =.046). A greater percentage of positive lymph nodes in the GEWF cases (49/82, 60%) were 0.5 cm or smaller compared with the non-GEWF cases (17/41, 41%). CONCLUSIONS: GEWF increases the yield of lymph nodes recovered from colorectal cancer specimens and may lead to improved staging of this cancer; it is inexpensive and simple to 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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".