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Record W2979463637 · doi:10.4095/314925

Science-based dredge disposal guidelines for port expansion

2019· report· en· W2979463637 on OpenAlexaffabout
Gwyn Lintern

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsPort (circuit theory)DredgingEnvironmental scienceEngineeringGeologyOceanographyElectrical engineering

Abstract

fetched live from OpenAlex

Coastal energy infrastructure and other port projects require dredging to make the sites suitable for construction. On the west coast of Canada, dredging has been required at many recently proposed port sites. Environment and Climate Change Canada (ECCC) licences disposal of material at several large disposal-at-sea (DoS) sites on the coast. Proponents may also propose a new or temporary DoSsite nearer to their development to save enormous shipping time and costs. Depending on the level of contamination of the sediment to be disposed, and the methods used, the regulation may require sediment to be disposed at either a dispersive or non-dispersive site. In the past several years, "guidelines for determining dispersivity" have been proposed by NRCan(Lintern)/EC scientists and stipulated to two proponents. The validity of the methodology is being tested. NRCanis part of a triparty Regional Ocean Disposal Advisory Committee that will investigate several aspects of dredge disposal on the coast, one of which is dispersivityof existing sites. NRCanis tasked with determining dispersivityat existing sites and with conducting sensitivity analysis of the variables used in the existing guidelines. This requires oceanographic mooring instrumentation, data analysis and modeling.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.374
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.077
GPT teacher head0.337
Teacher spread0.259 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes2
Has abstractyes

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