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Critical Shear Stresses of Sunken Oils

2014· article· en· W2165444660 on OpenAlexaboutno aff
Charles Bruno Richter Watkins, Olivia Jobin, Nancy E. Kinner, Thomas P. Ballestero, Neil Thomas, Robert Nothnagle

Bibliographic record

VenueInternational Oil Spill Conference Proceedings · 2014
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyFlumeShear (geology)Geotechnical engineeringShear stressCrude oilSink (geography)Hydrology (agriculture)Petroleum engineeringMaterials scienceGeographyPetrologyComposite materialCartography

Abstract

fetched live from OpenAlex

As observed in several recent cases (e.g., DBL-152, Enbridge-Kalamazoo), under certain circumstances, spilled oil can sink to the bottom of a water body. Once on the bottom, the oil can move or even remobilize into the water column. The critical shear stress (CSS) is used to accurately predict the movement of sunken oil along and off the bottom. Unfortunately, shear stress has only been measured for one sunken oil (Hibernian Crude API = 34). The Coastal Response Research Center (CRRC) at the University of New Hampshire (UNH) has an annular flume equipped with high-definition cameras and an acoustic velocimeter that can be used to estimate CSS by measuring the instantaneous, three-dimensional water current velocities at which sunken oils move and erode as visible oil droplets. The results reported are for an Alberta bitumen, tested at temperatures between 5° and 28°C in freshwater.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.293
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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