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Record W2403999699

Pulse: More than half of MDs under age 35 now using PDAs

2003· article· en· W2403999699 on OpenAlexvenueaboutno aff
Shelley Martin

Bibliographic record

VenueCanadian Medical Association Journal · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetMedicineFamily medicineGerontologyWorld Wide WebComputer science
DOInot available

Abstract

fetched live from OpenAlex

Results from the CMA's 2003 Physician Resource Questionnaire (PRQ) indicate that a third of Canadian physicians are now using a personal digital assistant (PDA) or wireless device such as a Palm Pilot in clinical practice, a 73% increase from the level of 19% recorded in 2001. In the 2002 PRQ, 28% of doctors reported using the devices. Use is highest among younger doctors, with more than half of those under age 35 (53%) now using a wireless device in clinical practice, compared with 15% of physicians aged 65 and older. Elsewhere on the electronic front, 17% of Canadian medical practices now have a Web site, the same proportion as in 2002. They are most popular among medical specialists, 25% of whom have launched sites. After increasing from 41% in 1997 to 89% in 2002, the proportion of physicians who personally use the Internet now appears to have levelled off at 88%. Physicians under age 35 are most likely to make personal use of the medium (96%), while those aged 55–64 and 65+ are least likely (83% and 71%). A large majority of physicians (90%) have had patients present medical information obtained on the Internet. At least occasionally, two-thirds of them (64%) refer patients to Web sites containing medical information. Those aged 65+ (47%) are least likely to do this. Even physicians who don't use the Internet refer patients to Web sites at least occasionally (33%), while 68% of MDs who use the Internet make these referrals. — Shelley Martin, Senior Analyst, CMA Research, Policy and Planning

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.019
GPT teacher head0.258
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2003
Admission routes2
Has abstractyes

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