Bibliographic record
Abstract
Canada Health Infoway (Infoway) was launched in 2001 following an agreement by Canada’s First Ministers to strengthen a Canada-wide health infostructure that would include the development and benefits of electronic healthcare solutions. With a goal to have an electronic health record (EHR) for 50% of all Canadians by population by 2010, Infoway is investing in some key areas of health information management (i.e., drug information, telehealth, laboratory and diagnostic imaging systems). Investments in systems to support the management of health information has necessitated a parallel investment in strategies to ensure that health professionals embrace these tools. The need to address the engagement of nurses, physicians and pharmacists in the use of EHR tools led to the creation of a Clinician Advisory team within Infoway. The mandate of this team is to liaise and work with relevant stakeholder communities to advance Infoway’s mission. More specifically, the team’s work is directed to
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 | 0.020 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.058 | 0.024 |
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".