Bibliographic record
Abstract
My entry into medical school coincided with the Web's entry into the popular culture. Indeed, prior to 1995 the Internet was the domain of academics and enthusiasts. Universities varied in their online offerings, although determined searching would turn up something somewhere in the world, whether at the NIH or in Argentina. Hand-held computers, of course, were still at the “fancy Filofax” stage of evolution. Fast forward 6 years. Every university now has a homegrown set of educational resources and links. Medical journals can be searched at portals like PubMed (www.ncbi.nlm.nih.gov/entrez/) and the CMA's own Osler site (www.cma.ca/osler), and accessed online. A number, including CMAJ (www.cma.ca/cmaj), have removed all access restrictions (www.freemedicaljournals.com). A variety of medical textbooks are also accessible online, as listed at Student Bookworld (www.studentbookworld.com/info/free/medical.htm) and MedicalStudent.com (www.medicalstudent.com). The British Medical Journal's collected resources (www.bmj.com/collections) include textbooks on the basics of statistics, epidemiology and reading the literature. Meanwhile, some dedicated souls have constructed impressive sites on their own. The one created by Dr. Ed Friedlander (The PathGuy, www .pathguy .com) contains pathology tutorials — including the approach to the unknown slide — definitions of medical vocabulary and summaries of general and systematic pathology for exam preparation. The Canadian Federation of Medical Students Web site (www.cfms.org) offers members access to details about CFMS billeting, a catalogue of national and international elective opportunities, discount airfares and CFMS awards. A page of links leads to sites for Canadian universities, medical societies, more online journals and textbooks and, of course, residency information. More informally, the Med-1 Survival Guide from McGill University, one of several online guides produced by McGill, presents the insider's view (www.med.mcgill.ca/~mss/guides/med1_guidebook/index.htm). No listing of survival tools would be complete without mention of hand-held computers. Such indispensable items as Harrison's Internal Medicine companion handbook, The Red Book, and the Intern Pocket Survival Guides are all available in electronic form (www .hand heldmed.com).
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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.152 | 0.174 |
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".