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Record W2218084189 · doi:10.1115/omae2015-41834

Ice Loads in Dry and Submerged Conditions

2015· article· en· W2218084189 on OpenAlexaff
Regina Sopper, Claude Daley, Bruce Colbourne

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsIndentationDry iceMaterials sciencePenetration (warfare)Dry sandGeologyComposite materialEngineering

Abstract

fetched live from OpenAlex

This paper describes a study of the effects of submergence on ice crushing loads. Thirty three small scale indentation tests have been performed on cone-shaped ice samples in dry and submerged conditions using a material testing system (MTS machine) located in a cold room at −7°C. The indenter was a flat aluminum plate at the bottom of a container that was attached to the actuator of the MTS machine. Transparent windows facilitated visual observations and recordings using a high speed camera. In the submerged tests the container was partly filled with salt water. Testing was performed at rates of 1 mm/s and 100 mm/s. The specimens were ice cones with 25 cm in diameter and with 20° and 30° angles. Data recordings comprised time-penetration and time-force histories. Generally higher forces were obtained in submerged tests. Furthermore, the difference between dry and submerged condition was more pronounced at the high indentation rate.

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)0.000
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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)0.0030.000

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 head0.018
GPT teacher head0.221
Teacher spread0.203 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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