North American Natural Gas Supply Forecast: The Hubbert Method Including the Effects of Institutions
Bibliographic record
Abstract
In this article, the U.S. and southern Canadian natural gas supply market is considered. An important model for oil and natural gas supply is the Hubbert curve. Not all regions of the world are producing oil or natural gas following a Hubbert curve, even when price and market conditions are accounted for. One reason is that institutions are affecting supply. We investigate the possible effects of oil and gas market institutions in North America on natural gas supply. A multi-cycle Hubbert curve with inflection points similar to the Soviet Union’s oil production multi-cycle Hubbert curve is used to determine North American natural gas discovery rates and to analyze how market specific institutions caused the inflection points. In addition, we analyze the latest shale natural gas projections critically. While currently, unconventional resources of natural gas suggest that North American natural gas production will increase without bound, the model here suggests a peak in North American natural gas supplies could happen in 2013.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".