Bibliographic record
Abstract
The 2019 virtual issue of the Health Information and Libraries Journal (HILJ) is published to link to the 2019 EAHIL Workshop taking place in Basel, Switzerland on 17-20 June 2019. The workshop is structured around six topics: (i) Roadmap of our Profession; (ii) Technology Uptake; (iii) Ecology of Scholarly Communications; (iv) Impact + Assessment; (v) Benchmarking + Advocacy; (vi) Evidence-Based Practice. These themes have been used to compile this virtual issue, which contains published articles selected from HILJ from the March 2019 issue through to June 2017. The virtual issue mirrors the format of a regular issue of HILJ, namely a review article, five original articles and articles from our three regular features: 'Dissertations into Practice', 'International Perspectives and Initiatives' and 'Teaching and Learning in Action'. The authors come from the UK, Canada, Australia, Italy, Iran and Belgium. All articles included in this virtual issue are available free online.
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 | 0.060 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.015 | 0.028 |
| Scholarly communication | 0.042 | 0.070 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.019 | 0.017 |
| Insufficient payload (model declined to judge) | 0.056 | 0.026 |
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".