Surgical treatment of stage I non-small cell lung carcinoma.
Bibliographic record
Abstract
In stage I non-small cell lung cancer (NSCLC), the cancer is localized to the lung. For this early stage NSCLC, therefore, surgery is considered to be the treatment of choice. In this report, we reviewed the surgical treatment approaches for stage I NSCLC, placing emphasis on limited resection and video-assisted thoracic surgery (VATS). In regard to limited resection, sublobar resection (wedge resection and segmentectomy) may yield a good long-term outcome in selected cases, as does lobectomy. No strong evidence to recommend this procedure has, however, been published. On the other hand, many descriptive studies have indicated that VATS may be useful for the treatment of NSCLC, although the results have not shown any statistically significant differences from those of resection by conventional open thoracotomy. In addition to the low invasiveness, the curability of NSCLC using the VATS approach has been recognized to be similar to that of the standard thoracotomic approaches in clinical practice. Well-controlled studies with strong statistical results are needed to provide strong supportive evidence for the use of VATS for NSCLC. (Ann Thorac Cardiovasc Surg 2003; 9: 283-9)
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".