<scp> CO <sub>2</sub> </scp> utilization in Eastern Canada: Sources, sites, and grid effects
Bibliographic record
Abstract
Abstract Achieving net zero carbon dioxide (CO 2 ) emissions will require the cessation of fossil fuel emissions into the atmosphere, yet the need for ‘fuel’ and energy storage will remain. One solution could be a carbon‐based fuel system where CO 2 of biogenic origin is converted to fuels using hydrogen generated by electrolysis powered by renewable energy sources. Methane has value as an initial target given its prevalence in biogas, use in home heating and in electricity generation. Sources of CO 2 in Eastern Canada are dominated by the iron and steel, cement, and aluminium industries, all of which have biogenic fuel options. Collecting all of the potentially biogenic CO 2 would displace 75% of current natural gas use and require a 50% increase in generating capacity. Initial efforts could site a carbon capture, utilization, and storage facility near Montreal, QC, with other large‐scale facilities near Hamilton, ON, and Lac St‐Jean, QC. These facilities would be grid connected and expected to operate ~6200 h annually. The most high‐frequency electrolysis events would be 10 h of run time and 2 h of idle time. These periods would peak during the equinox months and be at a minimum during the winter solstice. These operational assumptions will all be subject to the increased variability caused by anthropogenic climate change and increased renewable generation on the grid. A closed‐loop carbon‐based fuel system would require an equivalent price of $250 per tonne CO 2 .
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".