Production of Bio-Synthetic Natural Gas in Canada
Bibliographic record
Abstract
Large-scale production of renewable synthetic natural gas from biomass (bioSNG) in Canada was assessed for its ability to mitigate energy security and climate change risks. The land area within 100 km of Canada's network of natural gas pipelines was estimated to be capable of producing 67-210 Mt of dry lignocellulosic biomass per year with minimal adverse impacts on food and fiber production. Biomass gasification and subsequent methanation and upgrading were estimated to yield 16,000-61,000 Mm(3) of pipeline-quality gas (equivalent to 16-63% of Canada's current gas use). Life-cycle greenhouse gas emissions of bioSNG-based electricity were calculated to be only 8.2-10% of the emissions from coal-fired power. Although predicted production costs ($17-21 GJ(-1)) were much higher than current energy prices, a value for low-carbon energy would narrow the price differential. A bioSNG sector could infuse Canada's rural economy with $41-130 billion of investments and create 410,000-1,300,000 jobs while developing a nation-wide low-carbon energy system.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".