Bibliographic record
Abstract
The Research in the Workplace Award (RIWA)* is a biennial grant that seeks to fund small LIS-led workplace research projects. The award of £3000 GBP/$5900 USD/$6800 CAD aims to encourage and support those new to research. Projects can relate to any aspect of service provision, development or theory. Advice is available throughout the lifetime of your project, which should be achievable within 12 months. The award fund must constitute at least 55% of the overall project funding. If you have an idea for a small work-based research project, why not consider applying for RIWA 2006/7? A copy of the 2 page application form is available from: http://ifmh.org.uk/RIWA.html Submission deadline: 22nd December 2006. For further details contact Maria on +44 (0) 161 295 6423 or email: m.j.grant@salford.ac.uk * RIWA 2006/7 is sponsored by the National Library for Health CPD Forum, IFM Healthcare, the Health Libraries Group, the University Medical School Librarians Group, the University Health Sciences Libraries and Libraries for Nursing.
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 | 0.017 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.338 | 0.195 |
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".