Bibliographic record
Abstract
Cardiac catheterization is a key step in the diagnosisand management of coronary artery disease(CAD). Recent advances in percutaneous coronary interventions (PCI) and coronary artery bypass grafting (CABG) have enhanced options for the management of patients and have led to considerable expansion of the availability of cardiac catheterization across Canada and elsewhere. Whether our catheterization rates are appro-priate has been debated for almost 2 decades. In 1988/89, the average rate in Canada was 236 per 100 000 (range 194 in the Atlantic provinces to 280 in Alberta).1 A recent re-port has shown much higher rates across the country (e.g., 500 per 100 000 in Ontario in 2001/02) that are compara-ble to many in European countries but are still consider-ably lower than rates in the United States.2,3 The question remains: Are Canadian catheterization rates optimal, too low or too high? In this issue (page 35), Graham and colleagues4 attempt to determine the optimal population rate for cardiac catheterization. Using data collected between 1995 and
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 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.018 | 0.015 |
| Insufficient payload (model declined to judge) | 0.152 | 0.060 |
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".