The impact of national holidays on postoperative radiotherapy: A study from Canada
Bibliographic record
Abstract
ead and neck cancer is one of the top 10 most common cancers worldwide, accounting for over 660,000 new cases and 325,000 deaths each year.There are more than 30 areas within the head and neck where cancer can develop, including the mouth and lips, throat, voice box, and salivary glands.Mouth cancer tends to be the most frequently diagnosed form of head and neck cancer.Treatment is complex and depends on factors such as the type and location of cancer, the age of the patient, and patient performance status (the ability to perform certain activities of daily living such as self-care, housework, and physical activity).Many patients undergo surgery to remove the area affected by cancer, followed by postoperative radiotherapy (PORT), sometimes alongside chemotherapy.PORT is often used in patients when there is a high risk of the cancer returning.Globally, the five-year survival rate for head and neck cancer is around 50%.Dr Derek Wilke, radiation oncologist at the Nova Scotia Cancer Centre, and an assistant professor at Dalhousie University in Canada, highlights that prognosis can be improved by starting PORT within 6-7 weeks after surgery.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".