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Record W2905603826 · doi:10.5547/01956574.41.1.wwal

Pipeline Capacity Rationing and Crude Oil Price Differentials: The Case of Western Canada

2020· article· en· W2905603826 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Energy Journal · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBarrel (horology)Pipeline transportCrude oilRevenueCrack spreadAgricultural economicsEconomicsRationingPetroleum industryUpstream (networking)Oil-storage tradePipeline (software)PetroleumDownstream (manufacturing)Capacity utilizationOil pricePanel dataNatural resource economicsEnvironmental scienceMonetary economicsFinancePetroleum engineeringOperations managementMicroeconomicsEconometricsEnvironmental engineeringEngineering

Abstract

fetched live from OpenAlex

This paper examines the impact of pipeline capacity constraints on the discount of Canadian oil prices relative to U.S. benchmark oil prices. Using a panel of monthly data for Canadian oil exporting pipelines, we estimate that price differentials between U.S. markets and Western Canada would increase by 3.6% for 1% increase in pipeline capacity constraints. Pipeline capacity constraints in Canada have resulted in an average loss of $5.53 for every barrel of crude oil exported to the U.S. between 2009 and 2017. In 2015 and 2016, the losses due to insufficient pipeline capacity were equivalent to 3%-5% of the Canadian oil and gas industry’s sales revenue and 69%-102% of its royalty payments to provincial governments. Western Canadian oil refiners and refined products’ consumers benefit from the depressed crude oil prices. However, the total gains captured by local refiners and consumers are much smaller than the losses of the upstream sector.

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.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.029
GPT teacher head0.197
Teacher spread0.168 · 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