Guidelines for Appropriate Use of the Internet, Electronic Networking and Other Media 1 Guidelines for Appropriate Use of the Internet, Electronic Networking and Other Media These Guidelines apply to all medical trainees registered at the Faculty of Medic
Bibliographic record
Abstract
Toronto, including undergraduate and postgraduate students, fellows, clinical research fellows, or equivalent. Use of the Internet includes posting on blogs, instant messaging [IM], social networking sites, e-mail, posting to public media sites, mailing lists and video-sites. The capacity to record, store and transmit information in electronic format brings new responsibilities to those working in healthcare with respect to privacy of patient information and ensuring public trust in our hospitals, institutions and practices. Significant educational benefits can be derived from this technology but trainees need to be aware that there are also potential problems and liabilities associated with its use. Material that identifies patients, institutions or colleagues and is intentionally or unintentionally placed in the public domain may constitute a breach of standards of professionalism and confidentiality that damages the profession and our institutions. Guidance for medical trainees and the profession in the appropriate use of the Internet and electronic publication is necessary to avoid problems while maintaining freedom of expression. The University of Toronto is committed to maintaining respect for the core values of freedom of speech and academic freedom.1 Postgraduate trainees are reminded that they must meet multiple obligations in their capacity as university students, as members of the profession and College of Physicians and Surgeons of Ontario, and as employees of hospitals and other institutions. These obligations extend to the use of the Internet at any time – whether in a private or public
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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 | 0.015 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.047 | 0.046 |
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".