Infection prevention and control protocols in dentistry - Canadian guidelines
Bibliographic record
Abstract
Introduction. A risk of transmission of infectious diseases has always been an inherent part of dental practice. Easily communicable respiratory and blood borne diseases have prompted dental communities to establish, evaluate, update and monitor infection prevention and control (IPAC) protocols and strategies (guidelines). The aim of this paper was to present Canadian standard protocols of infection prevention and control in dental offices, and compare them with similar guidelines available to dentists in Serbia. Method. A detailed overview of the most current IPAC guidelines and protocols provided by the College of Dental Surgeons of British Columbia in Canada has been summarized. In addition, the effect of the most recent Covid-19 pandemic on the current infection prevention and control measures in dental offices and future perspectives has been reviewed. Conclusion. Implementing infection prevention and control guidelines is essential part of practicing dentistry. Regulatory authorities have responsibility to establish and provide dentist with the most current IPAC protocols while dentists need to adopt up-to-date procedures and appropriately and consistently use them in everyday practice.
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 | 0.039 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".