Bibliographic record
Abstract
When I was a medical student and junior doctor in the early 1980s I saw many patients on the wards in hospital with this terrible illness for which we could do little. When the heart fails as a pump one of the main manifestations is accumulation of fluid due to retention of sodium and water by the kidneys which also malfunction as a result of reduced blood flow and other mechanisms. Fluid accumulation in the legs and lungs leads to swelling (peripheral oedema) and breathlessness. Reduced blood flow to the muscles also causes intense fatigue. Back in these early days diuretics which caused the kidneys to produce more urine and relieve fluid intention) and digoxin, a 200 year old plant-extract thought to stimulate contraction of the failing heart, were the only two treatments we had, except for the rare, young, patient who was lucky enough to get a transplant. Otherwise, I knew that around 7 out of 10 of those men and women I saw would be dead within a year. Even worse the last months of their lives were characterized by disabling symptoms and exercise intolerance making even ordinary everyday activities a struggle, if not impossible. Often patients were also readmitted to hospital because of acute worsening of their symptoms. Around the time I graduated from medical school USA and European investigators such as Jay Cohn, Gary Francis, Peter Harris, and Philip Pool-Wilson were beginning to unravel the pathophysiology—the disease mechanisms—of heart failure and starting to explore the possibility of finding new treatments for this condition.1,2 The picture that emerged was remarkable. Although the primary problem was of course weakness and failing of the contraction of the heart …
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".