Boreal Forest Fires Recorded in 3000 Yrs Arctic Delta Sediments
Bibliographic record
Abstract
Summary Boreal forest fires are an important component of the vegetation and carbon dynamics in the Arctic. Increased temperature triggered by anthropogenic climate change is intensifying the number and scale of spring and summer boreal fires. High resolution sedimentary archives hold the key to reconstruct reliable records of past biomass burning. We studied a 3 m-long piston core, and its corresponding multicore, located in the Beaufort Sea, in front of the Mackenzie River mouth (Arctic Canada). The core captures a 3000-yrs history of discharge from the Mackenzie River catchment and eolian input. Biomass-burning biomarkers (benzene polycarboxylic acids, BPCA1, and levoglucosan2,3, created during low-temperature biomass-burning) as well as microscopic charcoal (larger than 10 µm)4,5 were quantified to reconstruct past variation in boreal fires. They are linked to changes in vegetation reconstructed using pollen and biomarkers (lignin phenols). The combined information from multiple biomass burning proxies provide a unique late Holocene record of boreal fire activity in Arctic Canada, recording climatic events such as the Little Ice Age.
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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) | 0.000 | 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".