Development of a Protocol for Sampling Faecal Coliform Bacteria Originating from Manure in the Vadose Zone
Bibliographic record
Abstract
Abstract Contamination of water resources with components of manure is a significant concern in Ontario. One aspect is the potential for bacterial transport through the vadose zone to groundwater following field application of manure. One obstacle to characterizing the movement of faecal bacteria in the vadose zone is the sampling of soil solution for bacteria. Porous-cup suction samplers are commonly used in estimating solute transport through this zone. However, there is little information on the calibration of such samplers for estimating numbers of bacteria in soil solution. This paper reports an attempt to make such a calibration. Tests were carried out under laboratory conditions which simulated the sampling of soil solution under field situation. As the suction applied was less than the air entry value for the ceramic porous cups used, the saturation status of the medium surrounding the cups was only important in terms of the number of colonies-forming units collected and not whether they were detected. The results indicated that although there were limitations in the use of the porous-cup suction samplers for bacterial sampling because of filtration effects, such samplers could be used for field collection of faecal bacteria from soil solution in situations with contrasting initial boundary conditions.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.009 |
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".