Bibliographic record
Abstract
The chronology of events that have led to the preparation of this book is fascinating and unique. When people of my generation went to medical school they heard very little about the importance of the main artery to the brain. Stroke was universally considered as a consequence of intracerebral hemorrhage or intracerebral arterial thrombosis particularly of the middle cerebral artery. Even the angiographic identification of internal carotid artery stenosis and occlusion in the late 1920s and early 1930s by Moniz failed to stimulate the worldwide medical community to adopt this diagnostic breakthrough, and to focus on the internal carotid artery. Legitimate concerns about the potential hazards of the use of radioactive thorotrast, the contrast medium used by the pioneers, with its biological half-life of hundreds of years, and the custom of cutting down on the carotid artery deterred enthusiasm for the use of the procedure. In the 1940s Hultquist and Fisher carried out postmortem studies of the previously neglected portion of the extracranial carotid artery independently in Sweden and Canada. They identified this vessel as a common site of arteriosclerotic disease causing stroke. Almost coincident with these illuminating publications came the introduction of percutaneous angiography and the recognition of transient ischemic attack as a harbinger of stroke. All this accumulated knowledge led to a 1954 Lancet case-report by Eastcott and Rob at St. Mary's Hospital, London, describing the surgical removal of the diseased portion of a symptomatic carotid artery.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.336 | 0.215 |
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".