Phosphatic crusts as macroscopic and microscopic proxies for identifying archaeological animal penning areas
Bibliographic record
Abstract
This study introduces new macroscopic and microscopic evidence for identifying archaeological animal penning areas: phosphatic crusts. Despite the importance of herding activities for reconstructing the social, economic, and ecological aspects of ancient communities, evidence for animal penning areas has traditionally relied on faint architectural traces or microscopic indicators that are often challenging to identify in the field. By employing a multidisciplinary approach that combines field observations, geoarchaeology, lipid biomarker, and microbotanical analyses, this research examines the phosphatic crusts recently identified at the Middle Bronze Age (1650-1300 BCE) site of La Muraiola di Povegliano (Verona, north-eastern Italy). The analyses uncover the processes behind phosphatic crust formation, highlighting the key role of the concentration of animal ejecta in the cementation of the deposit by nanocrystalline partially carbonated hydroxylapatite. This multi-proxy approach further demonstrates that phosphatic crusts serve as crucial archives for investigating the use of space, livestock management (e.g., free grazing/confinement, livestock species, foddering), and human-animal-environment interactions. • Phosphatic crusts can be a reliable macroscopic indicator for livestock penning areas. • Livestock penning can form cemented deposits of partially carbonated hydroxylapatite. • Mineralisation of organic remains occurs rapidly after deposition. • Phosphatised deposits are significant archaeobotanical archives in well-drained contexts. • Guidelines for field identification and handling of phosphatic crusts are provided.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".