Lost in Translation: Supporting learners to search comprehensively across databases
Bibliographic record
Abstract
<strong>Abstract: Introduction:</strong> Health sciences librarians play the key role of expert searcher for knowledge synthesis research projects. When students and trainees conduct systematic reviews as academic assignments, academic librarians train learners to search comprehensively for evidence in multiple sources. <strong>Description:</strong> The authors created an electronic toolkit with handouts and a video tutorial to support instruction on translating search strategies to various databases. <strong>Outcomes:</strong> The toolkit was well received by users, who provided constructive feedback and reported an increase in comfort with translating searches. Refinements based on the assessment results will improve the tools and supplemental resources will address some gaps in coverage. Most users still expressed the need to consult with a librarian for further training and review of their searches. <strong>Discussion:</strong> Trainees who need to conduct their own comprehensive searches for academic work will benefit from a variety of training tools to suit different levels of experience and learning styles. Electronic instructional resources such as handouts and videos can effectively supplement hands-on training and feedback from a health sciences librarian.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".