Archaeometric Approaches to Red Ochre Exploitation in Neolithic Greece: From Kremasti-Kilada to Kitrini Limni and Beyond
Bibliographic record
Abstract
This paper approaches Greek Neolithic red ochres through three different archaeometric lenses. A macro lens zooms in on the site of Kremasti-Kilada, in the Kitrini Limni Basin, and examines its ochre nodules, their provenance, the ways they were processed, as well as the applications of the resulting colorant. A mid-range lens places the Kremasti materials within a regional framework by examining specimens uncovered at several neighboring sites in the same basin. Finally, a wide lens views red ochres from a broader Aegean perspective. Our comparative approach highlights some of the choices Greek Neolithic people made and did not make in the context of red ochre exploitation. Furthermore, it raises specific questions and hypotheses that can be explored with future systematic and contextual archaeometric investigations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".