MétaCan
Menu
Back to cohort
Record W2057183749 · doi:10.1139/t02-004

Case study of a relict iceberg scour exposed at Scarborough Bluffs, Toronto, Ontario: implications for pipeline engineering

2002· article· en· W2057183749 on OpenAlexvenueaboutno aff
David Jason Eden, N. Eyles

Bibliographic record

VenueCanadian Geotechnical Journal · 2002
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsIcebergGeologyOutcropSiltFrost heavingGeotechnical engineeringSimaPleistoceneBermGeomorphologyIce sheetPaleontology

Abstract

fetched live from OpenAlex

Ice scour is a common process on high latitude shelves and has been studied extensively though laboratory and numerical modelling. Direct observations of ice scours in outcrop are very rare. This paper describes a Late Pleistocene iceberg scour observable in soil cliff exposures at Cudia Park, Scarborough Bluffs, Toronto, Ontario. The structure is cut into a glaciolacustrine clayey silt, is about 10 m wide and 4 m deep, and is filled with sands deposited in shallow water. A description of the scour and a simplified finite element model of sub-ice scour soil deformation are presented. It is estimated that the Cudia scour was caused by a small iceberg with a mass of 0.04 Mt, in a water depth between 10 and 30 m, acting with a downward force of 5 MN, which is consistent with modern iceberg scours. The relevance of the Cudia scour to pipeline engineering (design burial depths) is demonstrated, with reference to the design methodology of the Centre for Cold Ocean Research and Engineering (C-CORE). The Cudia scour provides an additional outcrop example of a subscour bearing capacity-type failure and is the only outcrop example to date with lateral berm piles, which are a characteristic part of modern iceberg scours.Key words: iceberg scour, Scarborough Bluffs, pipeline engineering, finite element modelling, Pleistocene geology.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.021
GPT teacher head0.217
Teacher spread0.196 · 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 designSimulation or modeling
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

Citations36
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Underground StructuresFrench-language works237,207