Bibliographic record
Abstract
Colorectal cancer is common in the Western world; ~5% of individuals diagnosed with colorectal cancer have an identifiable inherited genetic predisposition to this malignancy. Genetic testing and rational clinical management recommendations currently exist for the management of individuals with a variety of colorectal cancer syndromes, including hereditary nonpolyposis colorectal cancer (HNPCC, also known as Lynch syndrome), familial adenomatous polyposis (FAP), MYH-associated polyposis (MAP), and the hamartomatous polyposis syndromes (Peutz-Jeghers, juvenile polyposis, and Cowden disease). In addition to colorectal neoplasia, these syndromes frequently predispose carriers to a variety of extracolonic cancers. The elucidation of the genetic basis of several colorectal cancer predisposition syndromes over the past two decades has allowed for better management of individuals who are either affected with, or at-risk for inherited colorectal cancer syndromes. Appropriate multidisciplinary management of these individuals includes genetic counseling, genetic testing, clinical screening, and treatment recommendations.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".