Dentistry during and after COVID-19 Pandemic: Pediatric Considerations
Bibliographic record
Abstract
This article is a rumination on the outbreak of the dreaded coronavirus disease-2019 (COVID-19) pandemic which has engulfed both the developed and the developing countries, thereby causing widespread global public health concerns and threats to human lives. Although countries have made varied efforts, the pestilence is escalating due to the high infectivity. It is highly likely that dental professionals in upcoming days will come across COVID-19 patients and SARS-CoV-2 carriers, and hence must ensure a tactful handling of such patients to prevent its nosocomial spread. Despite the avalanche of information that has exploded in relation to this rapidly spreading disease, there is a lack of consolidated information to guide dentists regarding clinical management including precautions to take materials to use and postprocedure care, during and after the COVID-19 pandemic. Available sources of information have been analyzed, while relying on peer-reviewed reports followed by information available from the most respected authoritative sources, such as WHO, Centers for Disease Control and Prevention (CDC), and ADA. This review aims to provide a comprehensive summary from the available literature on COVID-19, its insinuation in dentistry, recommendations that have been published, and the actual in-practice implications, so a plan can be formulated and adapted to the circumstances of each dental practice during the pandemic and the times to follow. HOW TO CITE THIS ARTICLE: Dentistry during and after COVID-19 Pandemic: Pediatric Considerations. Int J Clin Pediatr Dent 2020;13(4):399-406.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".