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Record W1990826708 · doi:10.4043/23792-ms

Physical Testing Method to Study Ice Keel Strength Limits During a Gouging Process

2012· article· en· W1990826708 on OpenAlexaff
Jim Bruce, Gerry Piercey, Andrew Macneill, Ryan Phillips, A Derradji

Bibliographic record

VenueOTC Arctic Technology Conference · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsCentre For Cold Ocean Resources Engineering
Fundersnot available
KeywordsKeelBermGeotechnical engineeringEngineeringRidgeLimitingGeologyMarine engineeringStructural engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract A test program, undertaken as part of a C-CORE led Joint Industry Program(JIP), was carried out to investigate the limiting strength and failuremechanisms of seabed gouging ice ridge keels. A test frame was designed, fabricated, commissioned and used in the test program. During tests, methodswere developed to build & test large size keel specimens, and surfaceprofile both keel and soil bed before and after test. Testing consisted ofloading the keel with a surcharge force and initiating a horizontal movement ofsoil bed until keel failure was observed. In total, nine keels weremanufactured and tested under a variety of initial confinement pressuresranging from 0 kPa to 75 kPa. Six tests were conducted with a gravel berm andsoil bed and three tests were conducted using a steel (rigid) berm face andgravel soil bed. A summary of the test results and key observations arepresented in this paper.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.282
Teacher spread0.256 · 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 designBench or experimental
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

Citations5
Published2012
Admission routes1
Has abstractyes

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