Bibliographic record
Abstract
I t is with great excitement that I write on behalf of the critical care community to celebrate the partnership between the Canadian Critical Care Society (CCCS) and the Canadian Respiratory Journal.Since assuming the role of Editor-in-Chief in 2011, Dr Peter Paré has championed the strategic direction that was charted by the executive of the Canadian Thoracic Society (CTS) and the previous Editor-in-Chief, Dr Nick Anthonisen.Their goal was to enhance the breadth and scope of the Journal to reflect the activities of the CTS and to embrace the work of other researchers and increase the impact of the Journal on practice (1).For the CCCS, this partnership represents an opportunity to celebrate the success of research in critical care and our ability to foster the development of young investigators.Critical care research in Canada has a rich history, including pioneers such as Peter Macklem, Charlie Bryan and Bill Sibbald, and the success of the Canadian Critical Care Trials Group (CCCTG).Since its inaugural meeting held at Emerald Lake (Field, British Columbia) in September 1989, the CCCTG has flourished under the leadership of Tom Todd, Deborah Cook and John Marshall.More recently, Paul Hebert has assumed the role of chair of the CCCTG and is looking toward solidifying its strategic direction.The CCCTG has achieved world acclaim and an enviable level of productivity through a remarkably 'Canadian' collegial approach that has led to the publication of more than 120 articles, including 14 in the New England Journal of Medicine.The work of the CCCTG complements the tremendous contributions in clinical, basic science and health outcomes research in critical care across this country.It is perhaps fitting, then, that the CRJ has made a place for critical care, given the contribution that Canadian critical care researchers have made to the world.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.014 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.008 | 0.023 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".