Bibliographic record
Abstract
You either have the religion or you don‚t. That sentiment seems to sum things up when it comes to those little hand-held devices known as PDAs (personal digital assistants). Doctors who use devices such as the Palm Pilot say they are the greatest thing since the stethoscope. Meanwhile, those on the outside shake their heads in amused scepticism. As Dr. Gordon Hollway, a physician in Marathon, Ont., puts it: ”I always used to have a bunch of different things in different places. I‚d also have some addresses scribbled in my wordprocessing or email software, and then I‚d forget to update my address book and I‚d be left wondering which one was the most up-to-date version. Or I‚d be somewhere and someone would talk about a meeting and I wouldn‚t be able to reschedule it because I didn‚t have my Daytimer. Now, as long as I bring [my PDA] with me, I know I‚ll have all the basics that I need.” Wherever you fall in this theological debate, there is no doubt these devices are spreading like mad, and particularly within medicine. And with the modern software and capabilities of the new models, they are literally becoming a doc‚s best friend. One of the best sites for all that is Palm in medicine is at (www.pdamd.com). This site includes links to medically oriented software, online forums, reviews, and even a set of testimonials from physicians who love their Palms. An entire section is devoted to selecting the right PDA and there is a set of tutorials on how to make the best use of your new technological wonder. Another great site is Healthy PalmPilot (www.healthypalmpilot.com), created by Toronto physician Eric Tam. As he explains things, it was his quest for ”near lab-coat weightlessness” that led him to start using a PDA. His site includes more than 500 downloadable software resources for the practising physician, everything from organizers and patient management tools to diagnosis databases and wellness software. For those who still think the whole PDA phenomenon is laughable hype, take a look at Jim Thompson‚s Silly Pages site (www.jimthompson.net). Thompson, an emergency physician from PEI, is a Palm prophet who provides lots of good PDA resources, but he also knows how to laugh at the whole thing. He asks: ”Do we really need to say things like, ’Hey, look what I got on my Palm last night.‚?” Good question. —
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 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.148 | 0.094 |
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".