Strategies for Prevention of Toxicity Caused by Platinum‐Based Chemotherapy: Review and Summary of the Annual Meeting of the Blood–Brain Barrier Disruption Program, Gleneden Beach, Oregon, March 10, 2001
Bibliographic record
Abstract
OBJECTIVES: To summarize the findings relevant to otolaryngology from the annual meeting of the Blood-Brain Barrier Disruption Consortium in Gleneden Beach, Oregon, March 10, 2001. STUDY DESIGN: Summaries are provided by the speakers, as well as related data from the published literature. Findings in otology and oncology regarding ototoxicity that were discussed at the meeting are included. RESULTS: Data considered included physiological research, animal studies, and clinical trials that relate to platinum-based chemotherapy and prevention of toxicity. CONCLUSIONS: The dose-limiting side effects of platinum-based chemotherapy are preventable, but questions about the effect of the protective agents on oncological efficacy remain. Strategies for prevention of chemotherapy-induced toxicity include temporal or anatomical separation of cisplatin or carboplatin from sodium thiosulfate, D-methionine, or N-acetyl-cysteine. Clinical application of these methods has begun. The mechanisms presumably involve free radicals or drug conjugation, or both. Understanding the role of free radicals in medicine is likely to become important in the future.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.006 | 0.002 |
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".