Establishing a reliable protocol to measure tongue sensation
Bibliographic record
Abstract
The relationship between tongue sensation and tongue function for speech, mastication and deglutition are growing areas of interest among rehabilitative professionals. To determine the potential effect that sensation has on function, it is imperative that, first, reliable and valid measures of tongue sensation be established. The aim of this study was to develop a protocol to test tongue sensation across a spectrum of sensory functions that included two-point discrimination, light-touch discrimination, thermal sensation, texture recognition, oral stereognosis and taste recognition. Materials tested within each domain respectively included: (i) the MacKinnon-Dellon Disk-criminator, paperclip and caliper; (ii) the Semmes-Weinstein monofilament and cotton wisp; (iii) dental mirrors and glass test tubes; (iv) spheres of textured acrylic resin on rods; (v) acrylic resin forms with differing shapes on rods and (vi) salty, sweet, sour, bitter and neutral solutions. Materials were tested on 40 healthy subjects between the ages of 20 and 55. The results from this study indicated that thermal, texture and taste sensations appear robust for accuracy and discrimination. Two-point discrimination and light touch seem to be influenced by location of stimulation on the tongue and force applied, whereas stereognosis was influenced by stimulus complexity. The results of this study indicate that clinicians may choose instruments as practical as paperclips and test tubes for testing two-point discrimination and thermal sensation, respectively. For the other sensations, it may be important to use more sophisticated instrumentation to control variables of force, surface area stimulated and assessing sensations in graded steps.
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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 | 0.038 | 0.041 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.011 |
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".