Mammalian tooth enamel functional sophistication demonstrated by combined nanotribology and synchrotron radiation FTIR analyses
Bibliographic record
Abstract
The teeth of limbed vertebrates used for capturing and processing food are composed of mineralized dentine covered by hypermineralized enamel, the hardest material organisms produce. Here, we combine scanning probe microscopy, depth sensing, and spectromicroscopy (SR-FTIR) to characterize the surface ultrastructural topography, nanotribology, and chemical compositions of mammal species with different dietary habits, including omnivorous humans. Our synergistic approach shows that enamel with greater surface hardness or thickness exhibited a more salient gradient feature from the tooth surface to the dentino-enamel junction (DEJ) one that corresponds to the in situ phosphate-to-amide ratio. This gradient feature of enamel covering softer dentine is the determining factor of the amazingly robust physical property of this unique biomaterial. It provides the ability to dissipate stress under loading and prevent mechanical failure. Evolutionary change in the biochemical composition and biomechanical properties of mammalian dentition is related to variations in the oral processing of different food materials.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".