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Record W2347063424

Response to Oil Sands Products Assessment

2015· article· en· W2347063424 on OpenAlexaboutno aff
Kurt Hansen, Mike Sprague, John Joeckel, Mark Rockley

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsOil refineryOil spillSAFEROil sandsPipeline transportCoast guardAsphaltEnvironmental scienceEmergency responsePetroleumEnvironmental planningRisk analysis (engineering)Waste managementEngineeringEnvironmental protectionBusinessEnvironmental engineeringGeographyGeologyComputer scienceComputer security
DOInot available

Abstract

fetched live from OpenAlex

Abstract : Domestic production of crude oil in North America has increased at a tremendous rate. Oil sands products (OSP), such as diluted bitumen (Dilbit) from Alberta, Canada, are subject to spilling during transport to domestic markets and refineries in the U.S. via pipeline, tank cars, or marine vessels. This report includes a qualitative risk assessment of potential spills of Dilbit and identifies initial response issues. Specifically, the following information, along with appropriate recommendations, are documented in this report: Geographic areas most at risk for spills and the prime routes of transportation in those areas. Techniques identified for response to surface oil and submerged oil spills that can address OSPs. Identification of what additional information the U.S. Coast Guard decision-makers need and what additional equipment or tactics responders need to prepare for Dilbit spills in waterways. How addressing these recommendations will provide more robust and safer response to future spills of Dilbit. A description of proposed tasks for future research efforts related to the recommendations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score1.000

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)0.0010.003

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 head0.020
GPT teacher head0.272
Teacher spread0.252 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2015
Admission routes1
Has abstractyes

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