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Record W2074991768 · doi:10.7901/2169-3358-2005-1-919

THE BEHAVIOUR AND TREATMENT OF ORIMULSION® BITUMEN STRANDED ON PEBBLE, COBBLE OR IMPERMEABLE SUBSTRATE SHORELINES

2005· article· en· W2074991768 on OpenAlexaff
Edward H. Owens, Gary A. Sergy, John R. Harper

Bibliographic record

VenueInternational Oil Spill Conference Proceedings · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsAlberta Environment and Protected Areas
Fundersnot available
KeywordsAsphaltCobbleSedimentPebbleGeologyPenetration (warfare)ShoreEnvironmental scienceGeotechnical engineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

ABSTRACT Bitumen from an Orimulsion® spill can strand on shorelines in the form or dispersed bitumen or coalesced bitumen. Wetness of the shoreline substrate is an important factor in the adhesion of the bitumen and this in turn significantly effects selection of a treatment technique. Stranded bitumen on the surface of a shoreline that remains wet and/or non adhesive can be removed relatively easily by a combination of low-pressure washing, flooding, and recovery, or by manual and mechanical removal techniques. When stranded on dry surfaces or when interfacial surfaces dry, then the bitumen will strongly adhere to shoreline substrates either in the form of thin coatings or thick deposits of bitumen that are difficult to remove. Heated, high-pressure seawater washing is effective but must be accompanied by flooding to minimize penetration into coarse sediments. Sediment relocation, sediment removal, wet tilling and natural recovery techniques are appropriate techniques under specific oiling conditions. Temperature greatly effects bitumen penetration into sediments. Where bitumen coatings or deposits form in subsurface sediments then treatment becomes extremely difficult, requiring sediment removal or techniques to bring oiling surface sediments to the surface for treatment.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
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)0.0010.000

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 head0.022
GPT teacher head0.263
Teacher spread0.241 · 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.

Study designOther design
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
Published2005
Admission routes1
Has abstractyes

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