Bibliographic record
Abstract
Tumour hypoxia is known to be associated with aggressiveness and poor response to treatment, which has stimulated the development of several methods able to detect hypoxic tumours. To date, only one method, the oxygen microelectrode, has been used to provide pretreatment measures of tumour oxygenation that correlate with local control and disease-free survival. In an effort to validate new methods, comparisons have been made between the Eppendorf oxygen microelectrode, the comet assay, and hypoxia marker binding in tumours of patients undergoing curative treatment or palliative radiotherapy. These comparisons suggest that tumours with median oxygen tensions below 10 mmHg have relatively high hypoxic fractions as measured by the comet assay (> 0.20). The fraction of cells that binds pimonidazole, detected in cells obtained by fine-needle aspiration biopsy, correlates well with the hypoxic fraction measured using the comet assay. However, in general, hypoxic fractions measured by the comet assay and pimonidazole binding correlate only poorly with Eppendorf measurements performed for the same tumour. Factors that might be responsible for these differences, and problems associated with measuring the 'relevant' hypoxic population are discussed.
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".