Bibliographic record
Abstract
Introduction -Increasingly, database vendors are allowing downloads of their products to personal digital assistants (PDAs). The Hospital Library at Capital Health in Halifax, Nova Scotia, has the opportunity to provide PDA versions of resources to our users. The purpose of this survey is to find out the current environment of PDA use among the medical residents as a basis for developing library training and support for this technology. Question -Are medical residents using PDAs, and if yes, what type of PDA are they using, what experience do they have using them, how do they think they will use them in a clinical setting, and what products do they think they will find valuable in their practice? Methods -A Web-based survey was developed using PollDaddy software. A message was sent to all the medical residents on rotation at Capital Health on 12 November 2008; the survey closed 12 December 2008. Setting -The survey was developed by the Health Sciences Library of Capital Health. Capital Health is an academic health centre in Nova Scotia, Canada. The medical residents are affiliated with Dalhousie University Medical School. Participants -The participants were medical residents currently working in Capital Health hospitals. There were 55 respondents. Results -The majority of respondents own a PDA and have more than 1 year of experience using the device. They use PDAs to look up drug information, for messaging, and to consult e-books. More than 90% of those surveyed use PDAs in their clinical practice. The Palm platform is used by 64% of respondents while the iPhone is used by 24%. Conclusion -Medical residents are using PDAs with a preference for the Palm platform. They are used for clinical decision making, and 61 different sources were listed as currently used by the medical residents. Implications for the library are to provide training for the Palm and to concentrate on resource-specific training, rather than basic training on how to use a PDA. Limitations -There are approximately 300 medical residents on rotation at any one time. We received 55 responses. We realized, too late, that people could select only one item for question 7 ("Which resources do you use?"). However, most respondents provided lists of titles of PDA resources for question 8.
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 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 | 0.041 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".