Field measurement and modelling of two-dimensional river mixing
Bibliographic record
Abstract
Wastewater treatment facilities commonly discharge effluent to large receiving streams. An effluent plume may easily extend for many tens of kilometres downstream of a discharge point. A characteristic of the effluent plume is the existence of significant transverse concentration gradients in the river as the discharged effluent slowly mixes with the river water. Within this two-dimensional, transverse mixing zone accurate delineation of the effluent plume is essential for water quality monitoring and for management of the receiving stream. The capability to mathematically model two-dimensional river mixing and to predict effluent plume concentrations is a valuable tool for water quality management. An overview of two-dimensional river mixing theory is presented. Tracer methods for delineating effluent plumes resulting from continuous or transient input to rivers are described, and the results of tracer studies conducted on the Athabasca River in western Canada are presented. A computer modelling procedure for simulating two-dimensional river mixing is described. Application of the model is explained and comparison of model output to measured tracer concentrations is presented.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".