Fine root decomposition in two subalpine forests during the freeze–thaw season
Bibliographic record
Abstract
Little is known about fine root decomposition during the freeze–thaw season. To characterize fine root decomposition during this time (from October 2006 to April 2007), a field experiment was conducted to examine the decomposition of fine roots (diameters of 0–1 and 1–2 mm) of Minjiang fir ( Abies faxoniana Rehd. & E.H. Wilson) and Asian white birch ( Betula platyphylla Sukaczev) using buried litterbags in their respective habitats in western Sichuan, China. Over one freeze–thaw season, 14%–20% of mass was lost and 12%–31% of C, 6%–36% of N, 15%–25% of P, and 37%–43% of K were released. These losses accounted for about 40%–55% of mass lost and 23%–54% of C, 23%–89% of N, 25%–42% of P, and 48%–58% of K released within the first year of fine root decomposition. The amount of mass loss and bioelements release during the freeze–thaw season correlated closely with initial substrate quality and bioelement traits. Compared with birch fine root, fir fine root decomposition could be influenced more by decomposition processes during the freeze–thaw season. Results suggest that fine root decomposition during the freeze–thaw season can strongly contribute to ecosystem C and nutrient cycling.
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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 | 0.001 | 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".