City landscape usage on dissolved organic matter along Willband Creek, Abbotsford, BC
Bibliographic record
Abstract
Dissolved organic matter (DOM) comes from the partial decomposition of organic material and from water-soluble particles released by living organisms. It is an important piece of the aquatic food chain which plays a role in ecosystem productivity, nutrient cycling, UV light penetration, and heavy metal transport (Baines & Pace, 1991, Downing et al., 2009, Jansen, Kalbitz & McDowell, 2014, McKnight et al., 2001, Saraceno et al., 2009, Stedmon, Markager, & Bro, 2003, Williams et al., 2013,Wright & Reddy, 2009). DOM is a major contributor to the forming processes of soil as well as feeding microbial metabolism in aquatic environments, and relies on the hydrologic regimes for transport through soils to aquatic systems. Various anthropogenic landscapes can potentially have a large influence on the ecosystem dynamics of DOM, both directly (e.g., agriculture) and indirectly (e.g., impervious surfaces) (Baines & Pace, 1991, Jansen, Kalbitz, & McDowell, 2014, Saraceno et al., 2009, Williams et al., 2013, Wright & Reddy, 2009). Willband Creek is located in Abbotsford, BC, Canada (figure 1). It drains an area over 69 km2 by the time it joins the Fraser River at Matsqui Slough and is an important salmon bearing watershed (DFO, 1999). The creek itself begins from a groundwater fed lake in a large urban park near the centre of town before passing through residential, park/natural, industrial, and agricultural land before exiting into the Fraser River, and is joined by side tributaries that come off of the multi-usage Sumas Mountain and passing through agriculture land (figure 2). As part of a larger project, the purpose of this study is to attempt to understand how the various cityscape uses affect the movement and concentration of DOM within a dynamic aquatic environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".