Summary Report of the Pre-Conference Workshop at CAG2017
Bibliographic record
Abstract
In February 2017, the Canadian Association on Gerontology and the Centre on Aging at the University of Manitoba applied for a Planning and Dissemination Grant from the Institute of Aging (CIHR). Several partners supported the application. These partners included: Public Health Agency of Canada (PHAC); Canadian Longitudinal Study on Aging (CLSA); AGE-WELL; Canadian Geriatrics Society; Canadian Gerontological Nursing Association; Transportation Option Network for Seniors; Active Aging Canada; Manitoba Association of Senior Centres; Active Living Coalition for Older Adults in Manitoba. In May of 2017, we were informed that we were successful in receiving funding for the Pre-conference Workshop to be held at the Canadian Association on Gerontology Annual Scientific and Educational Meeting. The theme of the Meeting being “Evidence for Action in an Aging World”. Planning for the Workshop included a meeting at the 2017 International Association of Gerontology and Geriatrics World Congress, with several of the partners mentioned above.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.269 | 0.128 |
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".