Estimating water use efficiencies for water management reform in Southern Alberta irrigated agriculture
Bibliographic record
Abstract
Water use technical efficiency (WUTE) and three definitions of water use economic efficiency (WUEE) were estimated for the four river sub-basins that encompass the 13 irrigation districts in Southern Alberta over a 5-year period: 2004–08. The average level of WUTE varied from 3.5 to 6.2 Mt dam−3. The gross economic value of crop production varied from Canadian (C)$345 to C$592 dam−3. The net economic value of crop production varied from C$163 to C$268 dam−3. The incremental increase in net value of crop production under irrigation over what it would have been under dry land conditions varied from C$130 to C$199 dam−3. Results indicated a relatively high degree of correlation among the three measures of WUEE. Since about three-quarters of the water consumed in the four sub-basins in Southern Alberta is used for irrigating crops, increasing WUEE will be critical for meeting growing demand from predicted increases in economic activity, population growth and environmental needs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".