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Record W3217319126

Testing of sorbent booms in containment configurations

2004· article· en· W3217319126 on OpenAlexaboutno aff
David Cooper, D. Velicogna

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2004
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsSorbentBoomContainment (computer programming)Environmental sciencePetroleum engineeringWaste managementEngineeringMarine engineeringForensic engineeringEnvironmental engineeringChemistryComputer scienceAdsorption
DOInot available

Abstract

fetched live from OpenAlex

Sorbent booms are used to contain and collect oil spilled on water. Environment Canada, the Canadian General Standards Board, and the American Society for Testing and Materials have introduced some protocols for sorbent booms, but in general, a definitive protocol for the testing of sorbent booms has been lacking. Sorbent boom tests have only shown the ability of the product to soak up oil, not contain it. This study identified performance characteristics of conventional and innovative sorbent booms designed for fast flowing waters. Most sorbent booms are effective at low flow rates for short periods of time. The main problem is that most booms are constructed with polypropylene which eventually takes on water and sinks, causing containment failures. New products are now available that address some of the deficiencies of traditional design. This presentation presented test results of traditional, innovative and prototype sorbent booms in fast and flowing water conditions. In particular, it examined water uptake and its effect on the ability of the boom to float. It also examined ultimate oil retention and containment capabilities. 4 refs., 2 tabs., 22 figs.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.202
Teacher spread0.192 · 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".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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