Bibliographic record
Abstract
Abstract Clear visualization of dental materials and technical procedures demonstrated in real time through videos adds another dimension to student learning that is not available from written/verbal descriptions or still images/teaching aids alone. This module includes a series of 11 short video clips that provide an introduction to the parts of a cast removable partial denture (RPD) and the steps involved in the surveying process. Surveying is an essential skill that dental students need to develop to evaluate and design cast RPDs. Verbal descriptions of surveying in lectures and written descriptions in RPD text books and laboratory manuals are insufficient to prepare second-year dental students learning how to survey a partially edentulous cast for the first time. These videos were produced to fill this gap and have received positive feedback from students and course instructors over the past three years. When students have viewed the videos before the first lab and can follow the videos while completing their first surveying exercise in the lab, they are able to quickly master the criteria used to measure competency in surveying. The videos can also be used to review concepts for students currently in the course and courses for the more advanced dental student.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.136 | 0.061 |
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".