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Record W2248939322

Is There a Relationship between Rubble Field Configuration and Submarine Formations

2009· article· en· W2248939322 on OpenAlexvenueaboutno aff
Anne Barker, G.W. Timco, S. Blasco

Bibliographic record

VenueNPARC · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsRubbleBermSubmarineGeologyField (mathematics)CaissonGeotechnical engineeringOceanography
DOInot available

Abstract

fetched live from OpenAlex

In the Canadian Beaufort Sea, ice rubble fields frequently form when sea ice is driven over and grounds on submerged, relic drilling berms. This is also true of ice interacting with natural shoals. These rubble fields can be extensive, extending up to a kilometre along the principle axis of formation. In this paper, the relationship between the type of submarine formation that initiates rubble field development and the ultimate dimensions of the rubble field is explored. The analysis shows that although there is reasonable consistency in rubble dimensions at a specific location, the dependence of the size of the rubble field on the number of days of moving ice, ice conditions, water depth and other environmental parameters make a generalization of a rubble size relationship difficult to define. Nevertheless, there is a general trend of a 1:1 relationship between the size of the rubble field and size of the submarine berm. The type of submarine berm, one built for a caisson versus a sacrificial island berm, did influence the final dimensions of the rubble field.

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)0.006
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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.234
Teacher spread0.211 · 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

Citations2
Published2009
Admission routes2
Has abstractyes

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