Immunotherapy: a new standard of care in thoracic malignancies?
Bibliographic record
Abstract
In May 2017, the second European Respiratory Society research seminar of the Thoracic Oncology Assembly entitled "Immunotherapy, a new standard of care in thoracic malignancies?" was held in Paris, France. This seminar provided an opportunity to review the basis of antitumour immunity and to explain how immune checkpoint inhibitors (ICIs) work. The main therapeutic trials that have resulted in marketing authorisations for use of ICIs in lung cancer were reported. A particular focus was on the toxicity of these new molecules in relation to their immune-related adverse events. The need for biological selection, currently based on immunohistochemistry testing to identify the tumour expression of programmed death ligand (PD-L)1, was stressed, as well as the need to harmonise PD-L1 testing and techniques. Finally, sessions were dedicated to the combination of ICIs and radiotherapy and the place of ICIs in nonsmall cell lung cancer with oncogenic addictions. Finally, an important presentation was dedicated to the future of antitumour vaccination and of all ongoing trials in thoracic oncology.
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 | 0.018 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.007 | 0.018 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.022 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".