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Record W2558963433 · doi:10.4043/27363-ms

Evidence for Movement Crushing and Recrystallization of Ice in the Keels of Scouring Icebergs

2016· article· en· W2558963433 on OpenAlexaffabout
Chris M. T. Woodworth-Lynas, Tony King

Bibliographic record

VenueArctic Technology Conference · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsCentre For Cold Ocean Resources Engineering
Fundersnot available
KeywordsKeelIcebergGeologyRubbleSeafloor spreadingIce shelfOceanographySea iceGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract When icebergs touch and scour through unconsolidated seafloor sediment the keel ice may fracture and crush, creating individual ice blocks that may rotate independently of each other under confining pressure. Blocks of ice also may be forced into and embedded in the seafloor beneath the keel. Evidence for these dynamic processes is presented based on seafloor features observed during submersible dives on the Labrador shelf in 1985 and later. Additional evidence for crushing and recrystallization of ice from the keel of a grounded iceberg is provided from thin sections of ice collected from growlers that floated to the surface after breaking free from the margin of the keel. The constant width of upslope scouring events, some traversing more than 20 m of bathymetric change on Makkovik Bank, clearly indicate that scouring keels remain relatively stable after initial crushing and modification of the keel as it first contacts the seafloor. Such stability is very likely the result of keel armouring, the action of ice protection by adhesion and freezing of coarse seafloor material into the keel. The mechanical removal of keel ice by crushing early in a scour event reduces iceberg draft so that the potential amount of drop-down of a scouring iceberg into an Excavated Drill Centre is reduced.

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)0.001
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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.258
Teacher spread0.210 · 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

Citations1
Published2016
Admission routes2
Has abstractyes

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