Anxious patients and new COVID-19 dental office protocol
Bibliographic record
Abstract
BACKGROUND: Dentists are one of the most at risk of COVID-19 (Coronavirus Disease-19) infection professional category. In fact, the performance of the various treatments could generate a large number of droplets and aerosols that could carry the viruses. Being SARS-CoV-2 (Severe Acute Respiratory Syndrome-Coronavirus-2) a virus that is transmitted mainly by close contact with the droplets that cannot be contained with the standard of protection measures used so far. Patients should go to the dental offices after a telephone triage agreed with the dentist. The aim of this study was to verify whether and how the new protocols could influence dental phobia in patients and how the COVID-19 infection is part of the experience of those who suffer from anxious spectrum disorders.METHODS: Generally, a person who suffers from anxiety disorders tends to avoid and/or postpone visits and dental sessions.RESULTS: The publication of the new protocols relating to the cleaning and disinfection of environments and surfaces, the use of new personal protective equipment (PPE), the questionnaires to be made by telephone and in the studio are a further element of concern or contribute to reassuring this type of patient.CONCLUSIONS: Further studies and clinical trials are needed to highlight these problems in patients.
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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 | 0.035 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.039 | 0.006 |
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".