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Record W2586635873 · doi:10.3724/sp.j.1226.2016.00451

Probable effects of heat advection on the adjacent environment during oil production at Prudhoe Bay, Alaska

2016· article· en· W2586635873 on OpenAlexaboutno aff
Stuart A. Harris

Bibliographic record

VenueSciences in Cold and Arid Regions · 2016
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsBayAdvectionEnvironmental scienceBeaufort seaArcticOceanographyGlobal warmingClimatologyGeologyClimate change

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.171
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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