How animal dung can help to reconstruct past forest use: a late Neolithic case study from the Mooswinkel pile dwelling (Austria)
Bibliographic record
Abstract
Abstract Animal dung analyses are a useful tool for vegetational studies. Preserved ruminant dung from archaeological layers offers a unique possibility for the reconstruction of past fodder management strategies, and further for studying the impact of fodder acquisition and pasturing on forests. In this case study we investigate the impact of Late Neolithic livestock keeping on the forest around the “Mooswinkel” pile dwelling at the Austrian lake Mondsee through the analysis of botanical macroremains, insect remains as well as microhistological analyses of botanical remains in animal dung. Seasonal plant parts in the dung point out that cattle, goats, and/or sheep were evidently kept inside the settlement during the winter for protection. During the daytime, they were allowed to forage around the settlement. Winter fodder consisted of dried leaf hay, hay from grasses and herbs, male flowers of early blooming bushes, and fresh twigs of evergreen species, such as fir (Abies alba), ivy (Hedera helix), and mistletoe (Viscum album).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".