Bibliographic record
Abstract
STK11 encodes for the protein liver kinase B1, a serine/threonine kinase which is involved in a number of physiological processes including regulation of cellular metabolism, cell polarity and the DNA damage response. It acts as a tumour suppressor via multiple mechanisms, most classically through AMP-activated protein kinase-mediated inhibition of the mammalian target of rapamycin signalling pathway. Germline loss-of-function mutations in STK11 give rise to Peutz-Jeghers syndrome, which is associated with hamartomatous polyps of the gastrointestinal tract, mucocutaneous pigmentation and a substantially increased lifetime risk of many cancers. In the sporadic setting, STK11 mutations are commonly seen in a subset of adenocarcinomas of the lung in addition to a number of other tumours occurring at various sites. Mutations in STK11 have been associated with worse prognoses across a range of malignancies and may be a predictor of poor response to immunotherapy in a subset of lung cancers, though further studies are needed before the presence of STK11 mutations can be implemented as a routine clinical biomarker.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.020 |
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".