The Water-Use Efficiency of Dairy Farming in Eastern Ontario: A Case Study
Bibliographic record
Abstract
An excel-based calculator (WatBal-Dairy) was created as a framework for wateruse accounting of dairy farm operations.The water-use of alfalfa was measured in situ and compared to Denitrification and Decomposition (DNDC) model estimates.Results highlighted the need to calibrate DNDC to Canadian growing conditions with the model over-estimating measured evapotranspiration (ET) (34.1%),net ecosystem exchange of carbon dioxide (11.8%) and biomass (9.7%), while under-estimating soil moisture (-12%).The WatBal-Dairy prototype was created using validated empirical models for cattle and barn water-use and tested using operational data including measured cattle intake and washwater from a working dairy farm near Ottawa.The farm water footprint was 1025.7 kg H 2 O kg -1 FPCM; precipitation (green water) accounted for 99.35% of the footprint and pumped (blue) water 0.45%.The field environment (crops and pasture) was responsible for 99.6% of farm water consumption, i.e. water made unavailable for other uses.
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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 | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".