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Fate of diluted bitumen spilled in the coastal waters of British Columbia, Canada

2019· article· en· W2984961917 on OpenAlexafffundabout
Sophia C. Johannessen, Charles W. Greer, Charles G. Hannah, Thomas King, Kenneth Lee, Rich Pawlowicz, Cynthia Wright

Bibliographic record

VenueMarine Pollution Bulletin · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsUniversity of British ColumbiaNational Research Council CanadaFisheries and Oceans Canada
FundersFisheries and Oceans CanadaGovernment of Canada
KeywordsOceanographySink (geography)EstuaryShoreEnvironmental scienceHydrology (agriculture)Context (archaeology)GeologyGeography

Abstract

fetched live from OpenAlex

There is public concern about the behaviour of spilled diluted bitumen (dilbit) in marine and estuarine waters. We provide a preliminary assessment of the results of laboratory experiments and models, in the context of environmental conditions in the coastal waters of British Columbia. Most dilbit spilled within this region would likely float at the surface and be transported to shore by winds and currents. Fresh dilbit is too light to sink in coastal waters. Highly weathered dilbit could sink where salinity is less than 14, typically only near river mouths and in the top 1-3 m of fjords after heavy rainfall. Subsurface plumes of weathered dilbit could re-emerge at the surface. Sinking oil-particle aggregates are unlikely to form in coastal waters. However, dilbit could be entrained below the surface by wave mixing during storms and to depths of 150 m by coherent mixing in the Haro Strait tidal convergence zone.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.002
GPT teacher head0.150
Teacher spread0.147 · 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 designObservational
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

Citations29
Published2019
Admission routes3
Has abstractyes

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