Life history parameters in acellular extrinsic fiber cementum microstructure
Bibliographic record
Abstract
Abstract Life-history parameters such as pregnancies, skeletal trauma, and renal disease have previously been identified from hypomineralized growth layers (incremental lines) of acellular extrinsic fiber cementum (AEFC). The precise periodicity of these growth layers remains vaguely approximated, so causal life-history explanations using tooth cementum cannot yet be rigorously calculated or tested. On the other hand, we show how life history parameters in AEFC can be identified by two contrasting elemental detection methods. Based on our results we reject the possibility of accurate estimation of pregnancies and other life history parameters from cementum using scanning electron microscopy alone. Here, we propose a new methodological approach for cementum research, Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS), to measure degree and distribution of mineralization of cementum growth layers. Our results show that Tof-SIMS can significantly increase our knowledge of cementum composition and is therefore a powerful new tool for life history researchers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".