Probable effects of heat advection on the adjacent environment during oil production at Prudhoe Bay, Alaska
Bibliographic record
Abstract
The latest available data for mean annual air temperature at sites away from the Arctic coast in both Alaska and the Yukon Territory show no significant warming in the last 30~50 years. However, around the Arctic coast of northwest North America centered on Prudhoe Bay, the weather stations show significant warming of both the air and the ocean water, resulting in substantial losses in sea ice west of Prudhoe Bay. These changes appeared shortly after the commencement of shipment of oil through the Trans-Alaska Pipeline in 1977, but have now reached a quasi-stable thermal state. Since more than 17 trillion barrels of oil have passed through the pipeline after being cooled by the adjacent air, which in turn, can then result in the melting of the adjacent sea ice, there appears to be a very strong relationship between these events, and a marked lack of correlation with the changes of the content of greenhouse gases in the atmosphere. This contrasts with the IPCC interpretation of the available climatic data, which assumes that the maximum climatic warming at Prudhoe Bay is typical of the entire region and is the result of increasing greenhouse gases. Engineers need to consider heat advection by oil or gas from underground when designing pipeline facilities, and to take account of the potential environmental consequences that they may cause.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".