Estimating the Incremental Gross Margins due to Irrigation Water in Southern Alberta
Bibliographic record
Abstract
In this study, the gross margins (above variable costs) are estimated in Canadian dollars of 16 important irrigated crops in Southern Alberta over the years 2004 to 2008. The residual method is then used to estimate the total incremental gross margins (gross margins from irrigated crops minus estimated gross margins from dryland crops had irrigation not been available) of using water to irrigate agricultural crops in four sub-basins in Southern Alberta over those years. The annual incremental gross margins averaged $244 million (in 2008 Canadian dollars) per year and varied from a low of $218 million in 2007 to a high of $271 million in 2005. On a per hectare planted basis, the annual average gross margin from irrigated cropping was $590 and the incremental gross margin was $495. The average annual gross margin and incremental gross margin per 1000 m3 were $225 and $191, respectively.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".