Bibliographic record
Abstract
In response to Nguyen and Palma’s submission arguing that radiological suspicion of a local recurrence can be sufficient indication to proceed to salvage therapy, it is clear that despite efforts from several international groups, distinguishing recurrent tumor from radiation induced lung injury (RILI) using radiological evidence, such as CT or FDG-PET scans, is far from an exact science. The authors correctly point out that clinical practice in presumed medically inoperable stage I lung cancer allows for SBRT treatment without biopsy confirmation, for lesions with radiological features strongly suggesting malignancy. However, they are proposing that this approach could be reasonably extended to salvage therapy following SBRT. We contend that the therapeutic ratio, i.e., risk versus benefit, is substantially different for initial SBRT treatment versus post-SBRT salvage treatment, and thus we maintain that pathological proof of recurrence be obtained wherever reasonable.
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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.019 | 0.039 |
| Insufficient payload (model declined to judge) | 0.010 | 0.015 |
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".