Heterogeneity of colorectal adenomas, the serrated adenoma, and implications for screening and surveillance
Bibliographic record
Abstract
Current algorithms for screening and surveillance for colon cancer are valuable, but may be limited by the underlying nature of the targeted neoplastic lesions. Although part of the success of adenoma removal relates to interruption of so-called "adenoma-carcinoma sequence", an alternate serrated pathway to colon cancer may pose difficulties with the ultimate results achieved by traditional colonoscopic methods. The endpoint carcinoma in this unique pathway may be derived from a dysplastic serrated adenoma. These tend to be located primarily in the right colon, especially in females, and are frequently associated with co-existent colon cancer. Unfortunately, however, there are few, if any, other identifiable risk factors, including age or family history of colon polyps or colon cancer. Moreover, this alternate serrated pathway may itself also be quite biologically heterogeneous as reflected in sessile serrated adenomas (SSA) with virtually exclusive molecular signatures defined by the presence of either BRAF or KRAS mutations. Screening algorithms in the future may need to be modified and individualized, depending on new information that likely will emerge on the natural history of these biologically heterogeneous lesions that differs from traditional adenomatous polyps.
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 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".