Controlled feeding trials with ungulates: a new application of <i>in vivo</i> dental molding to assess the abrasive factors of microwear
Bibliographic record
Abstract
Microwear, the quantification of microscopic scratches and pits on the occlusal surfaces of tooth enamel, is commonly used as a paleodietary proxy. For ungulates (hoofed mammals), scratch-dominant microwear distinguishes modern grazers from browsers, presumably as a result of abrasion from grass phytoliths (biogenic silica). However, it is also likely that exogenous grit (i.e. soil, dust) is a contributing factor to these scratch-dominant patterns, which may reflect soil ingestion that varies with feeding height and/or environmental conditions (e.g. dust production in open and/or arid habitats). This study assessed the contribution of exogenous grit to tooth wear by measuring the effects of fine- and medium-grained silica sand on tooth enamel using a novel live-animal tooth-molding technique. It therefore constitutes the first controlled feeding experiment using ungulates and the first in vivo experiment using abrasives of different sizes. Four sheep were fed three diet treatments: (1) a mixture of Garrison and Brome hay (control), (2) hay treated with fine-grained silica sand (180-250 µm) and (3) hay treated with medium-grained silica sand (250-425 µm). We found a significant increase in pit features that was correlated with an increase in grain size of grit, corroborating earlier chewing simulation experiments that produced pits through grit-induced abrasion (i.e. the 'grit effect'). Our results support an interpretation of large silica grains fracturing to create smaller, more abundant angular particles capable of abrasion, with jaw movement defining feature shape (i.e. scratch or pit).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".