Particulate emissions from fires in central Siberian Scots pine forests
Bibliographic record
Abstract
Siberian boreal forest fires burn large areas annually, resulting in smoke that releases large amounts of particulate emission into the atmosphere. We sampled aerosol emissions from experimental fires on three Scots pine (Pinus sylvestris L.) forest sites of central Siberia. Emissions from ground-based aerosol samples were 0.10.7 t/ha. This value represented 1%7% of the total biomass (1030 t/ha) consumed during the experimental fires. We were able to classify the chemical composition of 77%90% of the mass of particulate fire emissions. Chemical analysis indicated that an average of 8%17% of the particulate composition was of mineral origin. Carbonaceous aerosols created because of incomplete combustion ranged from 50% to 70% of the total aerosol mass. The fraction of aerosols containing elemental carbon (EC) (i.e., graphite, soot, and charcoal) was 7%15%. As our samples were taken near the ground surface, these results represent freshly emitted fire aerosols that have not yet had time to react with atmospheric moisture or to undergo postfire chemical or physicalchemical changes. In a typical year, where 12 × 106 14 × 106 ha burn in Russia, we estimate that 3 × 106 10 × 106 t of particulate matter may be emitted into the atmosphere.
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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".