An Organ Culture Study of Frog Renal Tumor and its Effects on Normal Frog Kidney in vitro
Bibliographic record
Abstract
Adjuvant whole breast irradiation was established within the standard of care for breast-conserving therapy in the early 1980s, following the results of major randomized trials comparing mastectomy vs breast-conserving surgery and radiation. Since that time, techniques and treatment strategies have evolved, but one major thread that carries forward is the need to balance cost, efficacy, complications, and convenience. Fortunately, data from randomized trials conducted in Canada and Great Britain provide a solid framework for the consideration of hypofractionated radiation in the treatment of breast cancer. In this review we discuss the rationale and underlying radiobiologic concepts for hypofractionation, and review the clinical trials and American Society for Radiation Oncology (ASTRO) guidelines supporting this approach. We also review the practical considerations for treatment planning, including dosimetric criteria and how to approach treatment of the node-positive patient. In the current era of healthcare reform and cost awareness, thoughtful utilization of hypofractionation may offer considerable savings to individual patients and the healthcare system--without compromising clinical outcomes or quality of life.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".