A comparison of charcoal measurements for reconstruction of Mediterranean paleo-fire frequency in the mountains of Corsica
Bibliographic record
Abstract
Abstract Fire-history reconstructions inferred from sedimentary charcoal records are based on measuring sieved charcoal fragment area, estimating fragment volume, or counting fragments. Similar fire histories are reconstructed from these three approaches for boreal lake sediment cores, using locally defined thresholds. Here, we test the same approach for a montane Mediterranean lake in which taphonomical processes might differ from boreal lakes through fragmentation of charcoal particles. The Mediterranean charcoal series are characterized by highly variable charcoal accumulation rates. Results there indicate that the three proxies do not provide comparable fire histories. The differences are attributable to charcoal fragmentation. This could be linked to fire type (crown or surface fires) or taphonomical processes, including charcoal transportation in the catchment area or in the sediment. The lack of correlation between the concentration of charcoal and of mineral matter suggests that fragmentation is not linked to erosion. Reconstructions based on charcoal area are more robust and stable than those based on fragment counts. Area-based reconstructions should therefore be used instead of the particle-counting method when fragmentation may influence the fragment abundance.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".