Estimating the Age- and Season-of-Death for Wild Equids: a Comparison of Techniques Utilising a Sample from the Late Neolithic Site of Bad Buchau-Dullenried, Germany
Bibliographic record
Abstract
In this paper, various techniques for determining the age- and season-of-death of wild horse specimens are systematically compared using a sample derived from the Neolithic site of Bad Buchau-Dullenried, Germany. Tooth eruption and wear, crown height, manual optical analysis of dental cementum, line histogram analysis of dental cementum, and a new automated digital technique for analysing dental cementum are employed. Each tooth was measured, thin-sectioned, digitally photographed under microscopy, and the cementum layers analysed. The goal is to determine which technique is the most efficient (in terms of time and resources) and accuracy (in terms of age- and season-of-death) for analysts to employ. The data demonstrate that there is substantial variation between the techniques for determining the age- and season-of-death of individuals, and even between teeth of the same specimen. The results demonstrate that the digital automated technique has an advantage over conventional cementum increment counting in terms of reduced subjectivity, efficiency and accuracy for the identification of season- and age-of-death.
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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 | 0.001 | 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 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".