Bibliographic record
Abstract
Objective - The aim of this project was to complete an analysis of monograph and audiovisual items held in the Central Coast Health Service (CCHS) Libraries and containing information relevant to the treatment of acute stroke. Acute stroke is treated by multidisciplinary teams of clinicians based at two hospitals within the CCHS. The adequacy of the library collection was measured by subject coverage and age. Methods - The methodology used consisted of three main steps: a literature review; design, administration, and analysis of a questionnaire to members of the CCHS Acute Stroke Team; and an analysis of the libraries’ collections. The research project utilised project management methodology and an evidence based librarianship framework. Results - The questionnaire revealed that electronic resources were by far the most frequently used by participants, followed in order by print journals, books, interlibrary loan articles, and audiovisual items. Collection analysis demonstrated that the monograph and audiovisual collections were adequate in both scope and currency to support the information needs of Acute Stroke Team members, with the exception of resources to support patient education. Conclusion - The researchers developed recommendations for future collection development in the area of acute stroke resources. Conducting this project within the evidence based librarianship framework helped to develop library staff members’ confidence in their ability to make future collection development decisions, informed by the target group’s information needs and preferences. The collection analysis methodology was designed to be replicated, and new specialist groups within the client base of the library will be targeted to repeat the collection analysis process.
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 | 0.034 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.021 |
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".