Late Holocene deforestation of a tree line site: estimation of pre‐fire vegetation composition and black spruce cover using soil charcoal
Bibliographic record
Abstract
Anatomical identification of soil charcoal fragments was used to reconstruct the pre‐fire vegetation composition of a tree line site that burned ca 930 cal. AD in northern Québec, Canada. Soil charcoal was also used as a proxy to estimate black spruce Picea mariana palaeo‐cover. The site (a low‐elevated hilltop) is presently devoid of spruce trees and dominated by dwarf birch Betula glandulosa , lichens, ericaceous shrubs ( Ledum decumbens , Vaccinium vitis‐idaea ) and sedges. In contrast, black spruce dominated before the fire with an understory of Empetrum nigrum and Vaccinium vitis‐idaea . Pre‐fire black spruce cover was estimated at 32%, giving an indication of the potential for warming‐induced natural reforestation of the forest‐tundra.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".