Bibliographic record
Abstract
Sparking an interest in dentistry as a profession can come early in a student's life, perhaps even while as a young patient sitting in your dental chair. The Pre-Dental Program for undergraduates at Dartmouth College in Hanover, NH takes that ‘sparking' one step further.Several years ago, as a local dentist, retired private practitioner and member of the Dartmouth Medical school staff, I was asked to assume the responsibilities of meeting with Dartmouth students interested in dentistry. The result was a comprehensive mentoring program for students at the college. Each term, programs are organized with upper class members. Students meet over home cooked dinners or at the college to hear local practicing dentists share their journey into the profession and answer student questions. During the past 6 years the students have had the opportunity to speak with dental school admissions officers, dental clinical faculty and dental school deans.There is a mentoring process at Dartmouth that has been an effective pre-orientation for the students as they transition to dental school. They have had the opportunity to shadow local dentists in their dental offices and work at a local free dental clinic. Dental school programs where students can have a week or two immersed in the dental school setting with hands on opportunities to ‘feel' what dentistry is like has been a big help to those who have attended. The only programs that have been widely known to us have been the UMD New Jersey Gateway Program and one at UCLA.Through the American Academy of Gold Foil Operators, the American Board of Operative Dentistry, the Academy of Operative Dentistry and the American Academy of Restorative Dentistry, networking has been made possible with the clinical faculty at various dental schools in the US and Canada. These associations have been invaluable resources for helping students seek out good dental schools. They also learn the kind of questions that they could be asking during their interviews when seeking admission to dental schools.Practicing or retired dentists who live or work near colleges can offer their assistance to guide future dentists - giving them opportunities to learn, gain experience through shadowing in local dental offices, and be inspired. The thrill of being able to inspire excitement and interest in dentistry is a great feeling.Questions regarding starting a mentoring program can be directed via email to: dmdsmile@gmail.com
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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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.106 | 0.050 |
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".