Perspectives on the age and distribution of large wood in riparian carbon pools
Bibliographic record
Abstract
Most knowledge of carbon budgets is derived from the productivity and sequestration of carbon in terrestrial and marine ecosystems. Less is known of carbon stored in riparian areas associated with lakes and rivers. Case studies of the age distribution of carbon in aquatic large wood (C lw ) from two different landscapes with different drainage patterns were established using tree-ring and 14 C dating. Cumulative negative exponential distributions of the age of C lw ranged over periods from 1000 to 9485 years. Large woody debris had mean residence times of 261 years in small oligotrophic lakes and 350800 years in a stream reach. Large wood can reside for an order of magnitude longer in freshwaterriparian ecosystems than in comparable above-ground terrestrial ecosystems. Although riparian areas make up only a small fraction of most landscapes, they may account for a relatively larger proportion of aged C lw than is stored above ground in terrestrial ecosystems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".