Bibliographic record
Abstract
Studies like the International Early Lung Cancer Action Program (I-ELCAP) (1) have revolutionized our understanding of early-stage lung cancer and its management. In their recent article (2), Flores and colleagues challenge us with the notion that sublobar resection without mediastinal lymph node sampling may be an adequate treatment for clinical stage IA non-small cell lung cancer (NSCLC). Drawing on the database of the I-ELCAP project (1), they were able to stratify patients into two propensity matched cohorts who received mediastinal lymph node resection (MLNR) and those who did not. A solid statistical and survival analysis methodology failed to demonstrate any significant difference in overall survival between patients who received MLNR during their operation, and those who did not. The authors conclude that subsolid nodules less than 30 mm in diameter, and peripheral solid nodules less than 20 mm in diameter should be treated with sublobar resection without MLNR.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.134 | 0.075 |
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".