Bibliographic record
Abstract
Before discussing recent advances in radiation therapy, it is important to consider the basic principles. The design for a proper course of radiation therapy must consider the extent of extrathyroidal disease and the location of lymph node disease, as well as the radiation tolerance of normal tissues and organs. The accepted terminology to describe the radiation dose and target volume in the planning of radiotherapy is summarized in Table 1. The principle is to deliver the prescribed dose to the entire clinical target volume (CTV) with a reasonable dose uniformity (±5%). Customdesigned fields should be used to conform to the target volume while keeping the volume of irradiated normal tissues to a minimum. In general, the aim should be to deliver 5000–6000 rad (50–60 Gy) to the CTV and 6000–7000 rad (60–70 Gy) to the gross tumor volume (GTV) in 1800– 2000 rad (1.8–2.0 Gy) fractions over 5–7 wk ( 1 – 6 ). External radiation therapy is delivered with linear accelerators generating X-ray beams in the megavoltage range of 4–25 MV (photons). These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.025 |
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".