Bibliographic record
Abstract
This article reports on the findings of two evaluation sessions for the Women's Health Matters (WHM) website, a women's health website developed by Sunnybrook and Women's College Health Sciences Centre and The Centre for Research in Women's Health. Participants were women, primarily between the ages of 20 and 29, well educated, and enrolled in university degree programs. They have been using the computer and Internet for years, in particular, E-mail andthe World Wide Web. While they conduct web searches, most are not health information seekers on the web. However, they have positive attitudes toward the delivery of health information on the Internet. Participants viewed the WHM website prototype in a computer laboratory. They then completed several search tasks and a questionnaire, and discussed their perceptions of the website in a moderated focus group setting. They found the text-based content on the WHM website interesting, easy to understand, and useful. However, they experienced difficulty navigating the website using the website's navigational elements - hypertext links and search engine. They wanted to see more graphical elements added to the website, as well as communications channels, such as newsgroups, listserves and chatrooms, provided they are moderated by health care practitioners. They were not favorably disposed toward advertising on health websites.
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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 | 0.028 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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; 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".