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Record W1593285552

Network Vulnerability Assessment of the U.S. Crude Pipeline Infrastructure

2012· dissertation· en· W1593285552 on OpenAlex
Michael D. Larrañaga

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCalhoun: The Naval Postgraduate School Institutional Archive (Naval Postgraduate School) · 2012
Typedissertation
Languageen
FieldDecision Sciences
TopicLeadership, Behavior, and Decision-Making Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPipeline (software)Vulnerability (computing)Crude oilCascadePipeline transportEngineeringOil refineryPetroleum engineeringComputer scienceComputer securityEnvironmental engineeringWaste management
DOInot available

Abstract

fetched live from OpenAlex

The potential for cascade failure of the U.S. crude oil pipeline infrastructure is analyzed using Model Based Risk Assessment software. The pipeline system that distributes crude oil to refineries across the United States has gained much media attention with President Obamas denial of a permit to complete a key portion the Keystone-XL pipeline that will carry oil from Alberta, Canada to the Cushing Oil Trading Hub (COTH) in Cushing, OK. The analysis identified the COTH as the primary critical hub. The COTH is one of the worlds major oil terminals. A disruption of the COTH, Midwest/West Coast oil distribution networks, or critical hubs would have far-reaching negative consequences affecting global trade. The analysis also identified regional differences in network resiliency and susceptibility to cascade failure. Protecting all 55,000 miles of the U.S. crude oil pipeline infrastructure from catastrophic failure is an unachievable goal, but protection of the network from cascade failure and a Black Swan event can be achieved by protecting network hubs. The results of this analysis should be used as a starting point to increase network resiliency and prioritize the use of resources to secure the crude oil pipeline network against cascade failure.

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)0.009
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.003
Science and technology studies0.0050.003
Scholarly communication0.0010.001
Open science0.0070.002
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0010.001

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 head0.075
GPT teacher head0.384
Teacher spread0.309 · 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