Bibliographic record
Abstract
Prediction of the radioresponse of individual tumors has been described as the Holy Grail of radiotherapy (1). An extensive literature on Holy Grail research suggests that those who sought it had no idea what they were looking for and, not surprisingly, that they never found it. The radiobiologists and radiation oncologists who met in Montreal on October 6–8, 1999, to address the topic of ‘‘The Prediction of Tumor Response to Therapy’’ were a more focused group with better prospects for eventual success. A number of studies have been published of predictive assays based on clonogenic or nonclonogenic determination of tumor cell survival after a test dose of radiation. The first speaker, Catharine M. L. West (Paterson Institute for Cancer Research, Manchester, UK), proposed in situ immunohistochemical detection of tumor protein expression as an attractive alternative to cell-based assays. Immunohistochemistry has the potential to yield data within 24 h after biopsy, but a drawback, which may be resolved with technological advance, is that the results are usually not quantifiable. DNA repair enzymes have been targeted as being key to the repair of radiation damage and to survival, and studies have been done correlating the expression level in tumor sections of the DNAPK subunits G22P1 (also known as KU70) and XRCC5 (also known as KU80) with radiation response and treatment outcome. For cervix carcinoma, expression of XRCC5 showed a positive but not statistically significant correlation with surviving fraction at 2 Gy (SF2), while 5-year survival levels for cervix cancer and head and neck cancer patients correlated with low expression levels of tumor G22P1. In contrast, in a study of breast lumpectomy followed by radiotherapy, local recurrence showed no correlation with either G22P1 or XRCC5 expression. Another DNA repair enzyme, apurinic/ apyrimidinic endonuclease (HAP1), is involved in repair of AP sites, which are among the most frequent lesions after radiation exposure and may reflect double-strand DNA breaks. HAP1 expression has been found to correlate with
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".