Bibliographic record
Abstract
Canada’s Drug Agency (CDA-AMC) recommends that Keytruda be reimbursed by public drug plans for the adjuvant treatment of adult patients with stage IB (with tumour[s] of 4 cm in diameter or larger), II, or IIIA non–small cell lung cancer (NSCLC) who have undergone complete resection and platinum-based chemotherapy and whose tumours have a PD-L1 tumour proportion score (TPS) of less than 50%, as determined by a validated test, if certain conditions are met. Keytruda should only be covered to treat patients aged 18 years or older who have a diagnosis of stage IB (with tumour[s] of 4 cm in diameter or larger), II, or IIIA NSCLC whose tumours have been completely surgically removed, who have received platinum-based chemotherapy, whose tumours have a PD-L1 TPS of less than 50% as determined by pathology testing, and who are in relatively good health (as measured by performance status). Keytruda should not be covered for patients who have received or planned to receive radiation therapy before or after surgery, and/or who are receiving other drugs before surgery to shrink a tumour or stop its spread. Also, Keytruda should not be covered to treat patients who have had previous treatment with drugs that change how the immune system works. Keytruda should only be reimbursed if it is prescribed by clinicians with expertise in managing lung cancer and the price of Keytruda is reduced.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 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".