Nine-years effect of harvesting and mechanical site preparation on bryophyte decomposition and carbon stocks in a boreal forested peatland
Bibliographic record
Abstract
The data and code were used to assess the nine-year effects of silvicultural treatments of different intensity (harvesting and harvesting followed by mechanical site preparation) on the decomposition rates of common bryophyte’s species and on soil C stocks. The study area is located in the Clay Belt region of northwestern Quebec (Canada). There are two databases related to: (1) decompostion rate and (2) to soil C stocks. The first database contains 487 mass loss percent of three bryophytes species (Pleurozium schreberi, Sphagnum capillifolium, and Sphagnum fuscum) for one and two growing seasons (i.e., 4 months and 16 months, June to October 2019 and June 2019 to October 2020) and some micro-environmental variables. the microenvironmental variables involved, the Air and soil temperature, soil layer types (fibric, mesic, humic and mineral), water table fluctuations, organic layer thickness and canopy openness. The other database concerned soil carbon stock. There are 3 codes: one code regroups the analysis on decomposition, Principal component analysis and C stoks analysis. The second code on common variables declaration on data of decay rate and the last is on the path analysis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".