A life cycle inventory analysis of wood pellets for greenhouse heating: a case study at Macdonald campus of McGill University<sup>1</sup>
Bibliographic record
Abstract
Wood pellets are one of the most promising alternatives to fossil fuel in Canada. Using wood pellets for heating allows saving on heating source expenses as compared to fossil fuels. Moreover, direct carbon emissions from wood pellets are regarded as carbon neutral since regrowth of vegetation captures and stores carbon that already exists in the atmosphere. Using wood pellets as a heating fuel for greenhouse vegetable production is expected to result in less greenhouse gas emissions than fossil fuels. Increasing the domestic consumption of wood pellets for greenhouse heating in Canada would reduce the environmental impact of energy consumption. This study investigates the potential of using wood pellets as an alternative fuel for commercial greenhouses in Quebec. This study applied a life-cycle analysis to demonstrate the energy flows and environmental consequences of using wood pellets for greenhouse vegetable production. The results found that greenhouse gas emissions from wood pellets are lower than natural gas in greenhouse operations.
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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) | 0.001 | 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 | 0.001 |
| 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 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".