Oil, Natural-Gas, and NGL Endowment in North, Central, and South America
Bibliographic record
Abstract
Summary This study uses the United States Geological Survey (USGS) World Petroleum Assessment (USGS World Energy Assessment Team 2000) as a starting point. Then, it uses a previously defined variable-shape-distribution (VSD) model for estimating the endowment of oil, natural gas, and natural-gas liquids (NGL) throughout North, Central, and South America. Use of the VSD model is validated by an excellent fit with actual data, supported by coefficients of determination (R2) equal to 0.98 or greater. The study includes endowments in petroleum provinces not assessed previously by other organizations. Endowment, as defined by the USGS, refers to the sum of known volumes of hydrocarbons (cumulative production plus remaining reserves) and undiscovered volumes. Petroleum is the sum of oil, natural gas, and NGL. The importance of North, Central, and South America is highlighted by a hydrocarbon output during 2007 that accounted for 25% of the world oil production and more than 31% of the natural-gas production. It is concluded that there is a large petroleum endowment in North, Central, and South America that will last for several decades and will help to contribute significantly to the energy needs of these regions. It is recommended to actively pursue research and development of this endowment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".