The things you should have learned in dental school and never did (2007)
Bibliographic record
Abstract
The dental practice is a complex commercial and social microcosm for which almost all newly qualified dentists are ill-prepared. This is because most syllabi of dental schools do not cover the humanistic or business aspects of dental practice: many dental educators have never run full-time dental practices themselves. Most established and experienced clinicians acquire these practice management skills through trial and error, learning from their mistakes as they go along. This book is a valuable and concise guide for those who are just embarking on their dental careers and those in their first few years of practice. The author uses his experience and insight to provide useful information and guidance on a number of important practice issues such as communication with patients and staff, marketing, and career choices. His pragmatic and practical advice on interpersonal skills is interjected with humour and anecdotes which make the text very readable. It is often said that patients stay with the clinician not necessarily because of his clinical skills, but because of the relationship between them, and the ability of the professional and the practice staff to relate to patients' problems. There are plenty of tips here on empathizing with patients and managing the dental team, which even the experienced practitioner will find beneficial.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.094 | 0.048 |
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".