Bibliographic record
Abstract
This article is about my career path and my research. Hypoxia and imaging are the main themes. Hypoxia is a condition of low oxygen. I began as a comparative biochemist studying how species adapt to live in low oxygen conditions. Jobs looked tight in comparative research and so I moved into more medically applied research. I worked in one of the main laboratories developing what was then a new technology—MRI. I spent the rest of my career developing and applying MRI methods to study disease progression in a range of conditions including stroke, cancer, muscular dystrophy, multiple sclerosis, kidney disease, heart failure and high altitude exposure. I applied my knowledge of biochemistry and physiology to direct our MRI development research, which resulted in two ongoing programs: one was to study disease processes, the other to study technology development. Successes include a paper published in the journal PLoS One: “Training the brain to survive stroke”, where we stimulated natural hypoxia adaptive mechanisms in brain and showed that stroke outcome was greatly improved. Much of my work is in animal models but we translate technologies to patient care as well.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".