Modelling bacteria transport through vegetative filter strips
Bibliographic record
Abstract
Cropland runoff from manure applied fields and runoff from manure storage facilities may contribute significantly to bacterial contamination of streams and other surface water bodies in Ontario. Vegetative Filter Strips (VFS) are used to intercept the bacteria reaching surface water bodies. In this study a component for the transport of bacteria ('E.coli') through the VFS has been incorporated into the Guelph Design tool for VFS (GDVFS) model. Experiments were conducted to develop the partition coefficient for 'E.coli.' Processes simulated in the transport of free floating and particulate bacteria include infiltration, deposition, adsorption to vegetation and resuspension. Sensitivity analysis, calibration and validation of the model were performed using the data collected from the experiments. The model was found sensitive to the initial soil moisture content and performed better for free floating rather than for particulate bacteria. The incorporation of the bacteria component has increased the capability of the GDVFS in designing the VFS.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".