Mucous Membrane Color Assessment Variability of Veterinary Students Using Either Colorimetric or Word-Based Scales
Bibliographic record
Abstract
A colorimetric scale has the potential to be very useful as a training tool for students in veterinary training programs. The authors of this report hypothesized that clinically active, graduate level veterinary students would assess mucous membrane color with greater consistency using an image-based system than with traditional word-based techniques. Third- and fourth-year veterinary students were asked to evaluate 10 canine gingival mucosa images and rate them with either an image-based scale designed by the authors or a word-based system. Although the mean absolute deviations from the median values were greater for the word scale (0.22) than for the image scale (0.20) indicating increased variation, mixed model analysis did not demonstrate these differences were significant ( p = .120). Based on this data it is possible that prior image and word-based instruction made it easier for the students to differentiate mucous membrane colors, or that the majority of the students were multimodal learners rather than single-type learners, making previous instruction techniques effective regardless of whether they were visual or read/write based. The authors recommend that future investigators both evaluate previous student instruction and consider administering visual, auditory, read/write, kinesthetic (VARK) tests when investigating potential learning aids in veterinary medicine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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 teacher head, 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".