Economic analysis of tree-based intercropping in southern Ontario, Canada
Bibliographic record
Abstract
Tree Based Intercropping (TBI) integrates the use of crops and trees on the same land unit. Such systems can provide a variety of economic, environmental and social benefits in comparis on with mono-cropping agriculture system. The specific objectives of this thesis were to determine the productivity, profitability, and practicality of TBI systems relative to mono-cropping system in Canada. Predicting the productivity, profitability and practicality consisted of several steps. First of all, a comprehensive process-based mathematical model called Ecosys© were used to estimate the trees growth. Secondly, a economic analysis model (Farm-SAFE) was used to determine the profitability and feasibility of TBI system relative to mono-cropping system. The evaluation of mono-cropping and TBI systems was undertaken for selected tree and crop species. Selected tree species were hybrid poplar, Norway spruce and red oak and crops species were wheat, corn, soybean and barley. The results of this study suggested that TBI systems can under certain circumstances provide a productive, profitable and feasible alternative to mono-cropping system. Tree and crop production was invariably more efficient in the use of land when combined in TBI systems hybrid poplar than when separated in mono-cropping system. Farmers can use a combination of fast-growing specie (hybrid poplar) and slow-growing specie (red oak) simultaneously to increase their profit by using TBI agriculture system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".