Bibliographic record
Abstract
As I write this, the American Thoracic Society 2000 meeting held in Toronto has been over for a week. From every point of view it seems to have been a great success. While having the drawbacks of very large meetings, with some tiresome separation between different sessions, one could not complain about the depth of coverage, with over 6000 poster and slide presentations. I was particularly impressed with the number of senior researchers who took part and demonstrated amply that they were not merely names from the past but had much to offer research fellows, especially on a one‐to‐one basis. One could find standing in front of a poster ‐‐ Sol Permutt, Bob Hyatt, John West, Ann Woolcock, Neil Pride and many others who gave freely of their time, experience and wisdom. There can be no better meeting showcasing international respiratory research from all over the globe. The Canadian Thoracic Society (CTS) was prominent in the organization and presentation, and deserves to feel proud of the meeting′s success; the Society′s annual dinner was well and enthusiastically attended. At the dinner, Dr Clarence Guenter gave the Christie Lecture, which will appear in the Journal before the end of the year.
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 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.014 |
| Insufficient payload (model declined to judge) | 0.165 | 0.170 |
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".