Evaluating Water and Carbon Retention in a Low-Order, Designed River Corridor
Bibliographic record
Abstract
As urban residential areas expand into the areas around cities, especially in North America, these areas were previously forested or were converted to agricultural uses (e.g., cropping, grazing). Many of the pre-existing channels were modified prior to residential area expansion and required modification and/or restoration in order for development permits to be granted. These pre-existing channels are often low-order, semi-ephemeral streams with hydrological and geomorphological functions and provide aquatic-terrestrial habitat and ecological linkages. Once restored, these corridors provide important services to the entire river network related to flood-risk mitigation, sediment trapping, and are potential carbon (via particulate organic matter) sinks. This research evaluated water flow and carbon trapping within a low-order tributary of East Morrison Creek in Southern Ontario, Canada in the years immediately following construction. Water level records (5 September and 30 November 2019, and 1 April and 30 November 2020) show that even in its early development this new system was functioning efficiently. Sediment samples taken throughout the 2020 field season determined particulate organic matter was being stored, especially in features where flow was attenuated. Channel roughness imposed by large wood structures promote organic matter deposition within bed sediments and were expected to increase over time. These findings highlight the importance of spatial heterogeneity imposed by the design features used in this reach-scale restoration and serve as a valuable ‘proof of concept’ for future work along the urban-rural interface of expanding cities.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".