Bibliographic record
Abstract
30th anniversary in 2014.With a vision to publish, promote and disseminate the work of medical researchers in a manner that exemplifies the highest standards in research integrity, we have successfully established more than 10 Canadian journals.The first, The Canadian Journal of Cardiology, was sold to the Canadian Cardiovascular Society and is currently being published by a non-Canadian multinational.Today, we continue to publish six journals, all official publications of their respective Canadian medical societies.Each society receives a portion of revenues derived from the Journal.This includes Pain Research & Management, the official journal of the Canadian Pain Society, which is in its 18th year of publication.During these 18 years, we have published hundreds of studies serving the Canadian and international research communities, and the Canadian physicians who receive the Journal free of charge.It also serves advertisers well by providing access to specialists and general practitioners with an interest in this therapeutic area.Our business model has been symbiotic on many levels, with the publication of research being mainly supported by the pharmaceutical industry, which in turn benefits by increasing exposure to its products.This model, however, is in danger of unravelling… First, advertising support from pharmaceutical companies has decreased significantly over the past several years.And now, a second threat has appeared on the horizon.Currently, all advertisements aimed at Canadian physicians must be precleared by the Pharmaceutical Advertising Advisory Board (PAAB) and carry its logo, a process financed almost entirely by Canada's research-based pharmaceutical companies (Rx&D).Recently, PAAB, on an initiative of Rx&D, voted to replace all prescribing information (PI) with a combination of
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 | 0.014 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.019 | 0.016 |
| Insufficient payload (model declined to judge) | 0.081 | 0.064 |
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".