Bibliographic record
Abstract
Ann Woolcock graduated in medicine from the University of Adelaide and pursued postgraduate studies in respiratory medicine with Professor John Read at the University of Sydney. Her MD thesis, awarded in 1967, was on the mechanical behaviour of the lungs in asthma. From 1966 to 1968 she worked with Professor Peter Macklem at McGill University in Canada, then returned to the University of Sydney to continue researching asthma. Her work in asthma and epidemiology showed that asthma was caused by allergens but that there is a genetic component. Her clinical research was a major contribution to better outcomes in asthma, in particular, the demonstration and practical measurement of airway hyperresponsiveness and her subsequent research that examined its contribution to asthma severity and the ways in which treatments were able to reduce it. In 1989 she wrote, with others, the world's first national guidelines for asthma management, the Australian Asthma Management Plan. In 1984, she was appointed to a personal chair of Respiratory Medicine at the University of Sydney. She founded the Institute of Respiratory Medicine in 1985, based at Sydney's Royal Prince Alfred Hospital. After her death, the Institute was renamed the Woolcock Institute of Medical Research in her honour.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 0.014 |
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".