Bibliographic record
Abstract
Dental anxiety is considered the negative emotional state produced by the psychological response to uncomfortable or unpleasant stimuli. Individuals who suffer from dental anxiety tend to avoid seeking dental treatment. This often results in dental issues that lead to symptom-driven treatment which in turn increase the patients’ level of dental anxiety. A shoulder touch from a registered dental assistant (RDA) during the administration of local anesthetic for erupted third molar extractions is predicted to decrease anxiety more than a lead vest worn during administration. Participants will be randomly assigned into one of three conditions. The control group will have no intervention applied, the dentist (DDS) and RDA will proceed through administration of local anesthetic as they normally do within their practice. Participants in experiment group 1 will receive a moderate pressure shoulder touch by the RDA while the DDS is administering the anesthetic. Experimental group 2 will wear a lead vest during the administration of local anesthetic. All groups will be assessed pre and post-op using the modified dental anxiety scale (MDAS) to determine if the experimental groups have lower dental anxiety compared to the control group. It is predicted that physical touch will reduce anxiety in dental patients more than those in the control and lead vest groups. If the results demonstrate there is a greater reduction in anxiety with physical touch, an inexpensive and simple way to help decrease dental anxiety in patients will be identified. Faculty Mentor: Sean Rogers Department: Psychology (Honours)
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.043 | 0.007 |
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".