Bibliographic record
Abstract
Because pancreatic cancer has a poor survival rate and only 20% of patients present with potentially resectable disease, a key goal of therapy is to provide palliation. The poor medical condition of many patients interferes with their ability to tolerate traditional chemotherapy. Recently, however, a nucleoside analogue, gemcitabine, has been developed. This drug is more effective than 5-fluorouracil (5-FU), can be used in patients who fail to respond to 5-FU and has only modest toxicity. Combination therapies including gemcitabine and other agents are being tested. Local radiotherapy seems to provide pain relief, but gastrointestinal toxicity is significant. The effect of combined modality therapy (5-FU with radiotherapy) on survival is unclear, and it does not prevent local disease progression. Some novel biological agents, including angiogenesis inhibitors, matrix metalloproteinase inhibitors, antisense compounds, inhibitors of cell signalling such as epidermal growth factor and vascular endothelial growth factor, and inhibitors of oncogene activation, are undergoing phase II and III trials in patients with pancreatic cancer. Among the most promising are farnesyl protein transferase inhibitors, which modulate K-ras function. Such an approach is promising for the treatment of pancreatic cancer because this tumour frequently exhibits mutation of the ras gene.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".