Bibliographic record
Abstract
The North American natural gas (NG) market has been transformed by the emergence of unconventional gas development. With significant NG continental supplies the question has become, “How can industry, government and others work together to grow natural gas demand in the coming decades?” The Canadian Energy Research Institute (CERI) in collaboration with ICF International and Scenarios-2-Strategies (S2S) developed 4 scenarios depicting the influence of high/low NG usage for power generation, and high/low liquefied natural gas (LNG), export scenarios for both the United States (US) and Canada on North American NG market dynamics. The quantitative translation of the 4 scenarios resulted in two distinct but opposing outcomes. The scenarios based on significant LNG exports and a healthy economic recovery saw substantial short-term increases in Henry Hub (HH) gas prices supporting upstream production. However, increased LNG exports do not support the Canadian upstream industry with the exception of BC who was able to increase production dramatically in isolation to the rest of the country. Furthermore, Canada becomes a net-importer of NG from the US. The remaining 2 scenarios allow for end-users to increase their NG and for Canada to remain as an exporter to the US. The main conclusions of this report are that substantial LNG exports have the potential to drastically affect North American NG dynamics and there is more potential in the US than Canada to increase end-user NG demand growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.001 |
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".