Consilience in practice: social–ecological dynamics of the Lake Volvi region (Greece) during the last two millennia
Bibliographic record
Abstract
ABSTRACT The Lake Volvi area, part of the region of Macedonia (northern Greece), is a biodiversity hotspot, located in the central part of a major communication corridor connecting the western and eastern parts of the Balkans. The sediment succession from Lake Volvi is investigated here to provide a unique high‐resolution pollen and geochemical record for the last 2000 years combining palaeoecological and historical methods, implementing the concept of consilience. The palaeoecological data document the environmental dynamics since the occupation of the area by the Romans. The vegetation changes reveal the development of wetland habitats and the variations of the mixed deciduous oak and thermophilous–mesophilous forests, as well as cereal cultivation, grazing and arboriculture, whose intensity varied over time. Archaeological data are available for the 1st millennium ce, but detailed historical evidence becomes accessible from the 13th century ce onwards through Byzantine and Ottoman documents. Both historical and palaeoecological data indicate that the 16th century was the period of strongest population pressure on the environment of the Volvi region. However, for other periods, it is possible to observe disagreements between the proxies. We demonstrate that these contradictions can be resolved with a more complex understanding of the region's social–ecological dynamics.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".