Assessing the role of the EGF receptor in the development and progression of pancreatic cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Natalie Cook,1 Kristopher K Frese,2 Malcolm Moore11Division of Medical Oncology and Hematology, 2Ontario Cancer Institute, Princess Margaret Cancer Centre, Toronto, ON, CanadaAbstract: The prognosis for patients with pancreatic cancer remains poor despite increased knowledge of its molecular genetics and histopathological progression. Pancreatic cancer is a complicated, heterogeneous tumor with several common genetic alterations. Aberrant epidermal growth factor receptor (EGFR) expression can be found in chronic pancreatitis and in preinvasive and invasive pancreatic cancer. Therefore targeting this receptor, through monoclonal antibodies or downstream inhibition of tyrosine kinase activity, has the potential to produce encouraging results. Despite this, the majority of targeted therapies against EGFR have not performed as expected in clinical trials of pancreatic cancer. Understanding mechanisms of resistance and identification of pertinent biomarkers of efficacy will likely lead to further optimization of EGFR-directed treatment. In this article, we discuss the role of EGFR in the development and progression of pancreatic cancer, mechanisms of action of EGFR-directed agents, and the future of epidermal growth factor targeted-therapy and research in pancreatic cancer.Keywords: epidermal growth factor receptor, therapies, resistance
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.
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 | 0.001 | 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 | 0.000 |
| 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 it