Unconstrained Extraction of Fossil Fuels and Implication for Carbon Budgets under Climate Change Scenarios
Why this work is in the frame
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Bibliographic record
Abstract
Hubbert's curve was first introduced to project future oil reserves and production in the US. In this paper, Hubbert's logistic function was used to estimate future production of fossil fuels in different regions of the world. The aim is to adequately fit historical data with minimum error, calculate the projected CO2 emissions that emerge from the unconstrained extraction of coal, oil and natural gas, and hence to determine the consumption of the available carbon budget. For some of the world regions considered, Hubbert's logistic function fits the data well, while others fail to fall under the bell-shaped curve due to factors not considered in the analysis, such as political decisions to restrict production. An overshoot of the carbon budget to limit global warming to 1.5 o C is expected by 2050 in the case of unconstrained production of all fuels, with major contributors being Asia & Pacific regions for coal, the Middle East for oil, and North America for natural gas. In the case of a 2 o C global warming scenario, the same major contributors again consume the available budget by 2040 except for natural gas production that stays below the threshold. This analysis emphasizes the importance of capturing and storing carbon dioxide emissions, and/or artificial limits on fossil fuel production to prevent dangerous climate change.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it