Litter-fall and decomposition in harvested and un-harvested boreal forests
Bibliographic record
Abstract
Litter fall and litter decomposition were examined in harvested and unharvested western Newfoundland balsam fir (Abies balsamea) and black spruce (Picea mariana) forests. Rates of litterfall in mature 70-year-old forests were 2.4 to 3.5 Mg ha−1 year−1, which was reduced to 0.2 to 0.3 Mg ha−1 year−1 following harvesting. In contrast, rates of black spruce needle, balsam fir needle, fine (<2 mm diameter) root, and moss (dominated by feather moss) litter decomposition were not affected by forest harvesting at either site during 24 to 54 months of field incubation in litterbags. Mass loss of balsam fir needle, black spruce needle, and moss (dominated by feather moss) were not significantly different indicating that moss forms a labile litter type in a forested setting.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".