Concept Dictionary and Glossary at MCHP
Bibliographic record
Abstract
The Manitoba Centre for Health Policy's Concept Dictionary and Glossary, and the Data Repository they document, broaden the analytic possibilities associated with administrative data. The aim of the Repository is to describe and explain patterns of health care and illness, while the Concept Dictionary and Glossary create consistency in documenting research methodologies. The Concept Dictionary alone contains detailed operational definitions and programming code for measures used in MCHP research that are reusable in future projects. Making these tools available on the internet allows reaching a heterogeneous audience of academic and government health service partners, epidemiologists, planners, programmers, clinicians, and students extending around the globe. They aid in the retention of corporate knowledge, facilitate researcher/analyst communication, and enhance the Centre's knowledge translation activities. Such documentation has saved countless hours for programmers, analysts and researchers who frequently need to tread paths previously taken by others.
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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.016 | 0.029 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.188 | 0.094 |
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".