Introducing RefAware: a unique current awareness product
Bibliographic record
Abstract
Purpose The purpose of this paper is to review RefAware, a new current awareness product introduced to the University of Calgary in September 2008. Coinciding with the product's launch, a team of three librarians was established to develop expertise with RefAware and promote it within the library and across campus. Design/methodology/approach A brief overview of current awareness tools leads into a discussion of key features available in RefAware, supplemented by a detailed section guiding the user through the product. In addition to highlighting key promotional undertakings, comparisons are drawn between RefAware and Ingenta, one of the earliest current awareness services used by the University of Calgary Library. Findings Benefits of using this current awareness tool include access to current and reliable information, ability to search within multiple disciplines on a predetermined topic, the convenience of receiving alerts when new information becomes available, and direct export to RefWorks. Limitations include inability to combine search profiles into one search string, cumbersome source list creation tools, inconsistent functionality when exporting citations, and lack of clarity with regards to classification of source names. Practical implications While its capability to simultaneously search through many new electronic publications makes it a multi‐disciplinary electronic journal, RefAware should be viewed as a complement to other research tools, not as a replacement. Originality/value An objective review of this new current awareness product for librarians is provided.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.012 |
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".