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Record W2320753666 · doi:10.1061/9780784412411.00024

Modeling Sediment Disposal in Inshore Waterways of British Columbia, Canada

2012· article· en· W2320753666 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEstuarine and Coastal Modeling · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Sediment Control
Canadian institutionsASL Environmental Sciences (Canada)
Fundersnot available
KeywordsSedimentInterimEnvironmental scienceNumerical modelsNumerical modelingSediment transportWork (physics)Hydrology (agriculture)GeologyEngineeringArchaeologyGeotechnical engineeringGeographyGeomorphology

Abstract

fetched live from OpenAlex

In support of the environmental assessment and regulatory approval process and as an interim guide for field work, a number of numerical modeling studies of sediment disposals were recently carried out by ASL Environmental Sciences Inc. at the designated/potential disposal sites in the inshore waterways of British Columbia, Canada, using the 3D numerical model COCIRM-SED and the short-term fate model of sediment disposal, STFATE. In these applications, STFATE was used to provide initial distributions of suspended sediment and bottom accumulation in detail, typically within the first hour of the sediment disposal operation, as a useful interim guide for field work and input to the 3D model COCIRM-SED, which was then adapted to examine the transport and fate of all disposal materials over much larger spatial scales and longer periods of time. This paper reports the model approaches and the detailed model results in the Brown Passage application.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score0.579

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)0.0000.000

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 head0.006
GPT teacher head0.166
Teacher spread0.161 · 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