Bibliographic record
Abstract
The CMA's 2002 Physician Resource Questionnaire (PRQ) has determined that the once yawning gap between physicians' personal computer use and personal Internet use has disappeared. In 1997, only 41% of physicians reported using the Internet even though 74% were using computers; today, both computer and Internet use by MDs stands at 89%. Among those who do not currently use the Internet, 31% plan to do so within the next year. Physicians in the youngest age groups are most likely to be online, with 96% of those under 35 and 94% of those aged 35–44 reporting that they use the Internet, compared with 82% of those aged 55–64 and 72% of those 65 and older. Female physicians are slightly less likely than males to use the Internet (87% vs. 89%), and urban physicians are slightly more likely to be online than their rural colleagues (89% vs. 85%). This year marked the first time the PRQ asked physicians if their practice has a Web site, and almost 1 in 5 (17%) do. Among those who do not, 7% plan to create one in the coming year. Medical specialists were much more likely to have Web sites (23%) than GP/FPs (13%) and surgical specialists (15%). Almost all physicians (90%) have had patients present them with medical information obtained on the Internet, up from 84% in 2000, and 20% refer their patients to medical Web sites weekly or daily, up from 14% in 2001; another 42% refer patients to the Web monthly or occasionally, up from 34% a year ago. This referral pattern is not restricted to physicians who use the Internet: of PRQ respondents who do not personally use the Internet, 27% still referred patients to medical Web sites. The PRQ is Canada's largest annual survey of the professional activities of physicians. The 2002 survey was mailed to a random sample of 7693 doctors, and the response rate was 38%. Results at the national level are considered accurate to within ±1.9%, 19 times out of 20. Tables from the 2002 PRQ are available at www.ecmaj.com/cgi/content/full/167/5/521/DC1. — Shelley Martin, Senior Analyst, Research, Policy and Planning Directorate, CMA
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".