Development and Testing of a Hydro-Chemical River MixingModel to Investigate Sources of Carbon and Mercury in the Mackenzie River Basin, Canada
Bibliographic record
Abstract
Mercury, Hg, is found in Arctic biota in alarming quantity, posing a potential health risk for the local population. It is believed that the large Arctic rivers contribute to this. The Mackenzie River annually transports approximately 325 km3 water to the Arctic Ocean, which is ca 10% of the freshwater received. The annual water flow also transports ca 2 ton of Hg. In order to investigate the source of Hg within the Mackenzie River Basin and the path of transport, a hydro-chemical river mixing model is constructed using field data gathered in summer 2018 and publicly available data. However, since the Hg concentration is very low in the river water and it is known that Hg binds very strongly to dissolved organic carbon (DOC) and particulate organic carbon (POC), both DOC and POC are utilized instead as proxies for Hg. The purpose of the model is to allow for estimations to be made of the relative contributions of different sub-basins and effluents to the total outflow of (e.g.) DOC at the mouth of the Mackenzie River, based on limited hydrographic and riverine water quality data. The model was used to estimate the mixing of DOC and POC sources for summer 2018 as an initial test of its performance. It performs adequately as it can estimate the amount of water discharge and DOC/TOC (total organic carbon) load that each node contributes to the Mackenzie River. The results from the model suggest that the contribution of organic carbon from each sub-watershed is not solely dependent on either drainage area size or water discharge; additionally, it appears to be determined by the local environment and geology. Water from catchment areas containing peatlands have high DOC content, and water passing through regions with coal layers have high POC content. The loss of POC towards the end of the model coincides well with the expected deceleration of the water discharge entering the Mackenzie River delta. It is concluded that the model should be useful for the study of Hg origin and transport in the Mackenzie River. Also, it has the potential for being a starting point for a more advanced or predictive model.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".