Bibliographic record
Abstract
Esophageal cancer is often diagnosed in its late stages with a 5-year overall survival rate of approximately 28% in British Columbia. It frequently presents as either squamous cell carcinoma or adenocarcinoma. The most common presenting complaint is dysphagia, typically characterized by a worsening tolerance to solid foods. Esophagogastroduodenoscopy with biopsy is the gold standard for diagnosis. CT scan of the chest and abdomen, FDG-PET scan, and endoscopic ultrasound are useful staging investigations. Esophageal cancer is a heterogeneous disease with no single optimal treatment algorithm. Esophagectomy is the preferred treatment modality in Tis-T1 disease. Neoadjuvant chemoradiotherapy prior to definitive surgery should always be considered in T2 disease and is recommended in ≥T3 or N+ disease. There is controversial evidence against the survival benefit and potential added morbidity of neoadjuvant chemoradiotherapy in the treatment of early esophageal cancer. Unresectable and cervical tumors should be treated with definitive chemoradiotherapy. The optimal treatment of adenocarcinomas of the distal esophagus and gastro-esophageal junction is under investigation but likely includes peri-operative chemotherapy. Current research in esophageal cancer includes the use of early FDG-PET scans to assess response to chemotherapy, which could have important implications in prognostication and treatment decisions. Keywords: localized esophageal cancer, management, chemoradiotherapy, FDG-PET
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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".