Exploring the Links Between Texture Perception and Bolus Properties Throughout oral Processing. Part 1: Breakdown Paths
Bibliographic record
Abstract
Abstract This study explored links between texture perception and breakdown path throughout oral processing. Five subjects chewed a short dough biscuit recipe. Dynamic textural perception was followed using Temporal Dominance of Sensations. Subjects expectorated at three stages of bolus formation (early, mid, and point of swallow). Visual inspection and moisture content (MC) provided a description of breakdown path. Interindividual differences in perceived texture and breakdown paths were observed. This study indicated differences between how individuals used sensory texture terms to describe bolus structure. The dry‐to‐sticky dominance transition corresponded to increased mixing and MC. However, there was not a significant change in MC for all subjects.A panel‐level analysis agreed with the “Mouth Process” model but there were interindividual differences at the point of swallow. This study suggests that there may not be a universal swallowing threshold for this biscuit recipe in terms of the measured properties but does indicate it may be possible to group consumers using bolus structure swallowing thresholds. Practical Applications Oral processing of a solid food involves food breakdown and reassembly with saliva into a deformable bolus that can be swallowed safely. The relationships between masticatory behavior, perceived texture, bolus structure, and mechanical and rheological properties throughout oral processing are still not fully understood. This study provides evidence of the subjective nature of oral processing and texture perception but indicates that each individual is not necessarily unique. Consumers may be able to be categorized into different groups based upon sensory dominance, bolus structure, and moisture content swallowing thresholds. Understanding these groupings could aid in the design of foods that follow a desired oral processing path and therefore provide consumers with a specific sensory experience.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".