Sturgeon River Watershed Aquatic Ecosystem Assessment
Bibliographic record
Abstract
The North Saskatchewan Watershed Alliance (NSWA) is responsible for making watershed management recommendations to local watershed partners and the Government of Alberta. The Sturgeon River (SR) is one of the 12 sub-watersheds within the larger North Saskatchewan River (NSR) watershed. Although the SR watershed covers a relatively large portion of the NSR watershed, comprehensive information regarding the aquatic ecosystem is not available. Thus, the North Saskatchewan Watershed Alliance (NSWA) commissioned CPP Environmental to conduct this survey to create a baseline and status regarding the aquatic ecosystems along the SR. The scope of this project included multiple ecosystem components, including water quality, physical habitat, macroinvertebrate community, and fish community. The purpose of measuring all of these components is to obtain a comprehensive view of the SR aquatic ecosystems, which each are communities of living organisms and their physical and chemical environment. The Sturgeon River (SR) was surveyed at twelve sampling stations distributed throughout the length of the river, as well as the main tributaries. At each sampling station on the SR, physical habitat, water quality, vegetation, fish, and macroinvertebrate surveys took place. In the tributaries, only water quality was measured. Water quality variables analyzed included nutrients (phosphorus and nitrogen), dissolved oxygen, suspended solids, pesticides, metals, and salts.
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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 | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".