Bibliographic record
Abstract
The Canadian Institutes of Health Research (CIHR) was officially established on June 7, 2000. Among the 13 institutes that were created, the Institute for Circulatory and Respiratory Health (C&R or CnR), which brings together researchers in the fields of heart, stroke, lung and blood research, has become the principal outlet for respiratory research in this country. Although this large, combined institute was not the first choice of our society or of the respiratory research community at large, we must respect this choice within the context of the new direction for Canadian health research and help to make it work. Over this past summer, the process of recruiting the scientific directors and advisory board members for each CIHR institute has proceeded at a rapid pace. As we go to press, the decisions on the appointment of the 13 inaugural scientific directors are being made. In addition, over the next few weeks, the institute advisory boards will be appointed. The CIHR Governing Council has the ultimate responsibility for these appointments. The Council represents a very broad cross‐section of the health research community in Canada; all of us on the Council sincerely wish to see the very best team of directors and board members selected to fulfill these roles.
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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.011 | 0.019 |
| Insufficient payload (model declined to judge) | 0.012 | 0.009 |
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".