Osimertinib in Stage III <i>EGFR</i> -Mutated NSCLC — Game, Set, Match
Bibliographic record
Abstract
Exactly 20 years ago, the precision-medicine revolution in lung cancer began with the discovery of sensitizing mutations in the epidermal growth factor receptor (EGFR) tyrosine kinase domain, 1,2 predicting dramatic patient benefit from EGFR tyrosine kinase inhibitors (TKIs). By 2024, routine testing for genomic alterations has expanded to nine genes with matched targeted therapies for advanced non–small-cell lung cancer (NSCLC) — EGFR , ALK , ROS1 , RET , MET , KRAS , NTRK , BRAF , and ERBB2 . More than half of patients with NSCLC have genomic alterations in tumor cells, including EGFR mutations in approximately 40% of patients in East Asia and 15 to 25% of those . . .
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.009 | 0.020 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".