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Record W6981935797

The Friction Coefficient of a Large Ice Block on a Sand/Gravel Beach

2003· article· en· W6981935797 on OpenAlexaffvenue

Bibliographic record

VenueNPARC · 2003
Typearticle
Languageen
FieldMaterials Science
TopicX-ray Diffraction in Crystallography
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsBlock (permutation group theory)Friction coefficientCoefficient of frictionStatic frictionDynamical frictionMode (computer interface)Measure (data warehouse)Function (biology)
DOInot available

Abstract

fetched live from OpenAlex

The amount of ice ride-up on beaches and shorelines is a function of the slope of the beach, the driving force, the size of the ice blocks, and the friction between the ice and the beach. Predicting the amount of ride-up is difficult, primarily because little is known about the friction coefficient of large ice blocks on sand/gravel beaches. To investigate this, a test program was performed to measure the friction of a large block of ice sliding on a sand/gravel beach. Four different friction coefficients were measured, corresponding to the four modes of movement of the block on the beach: static, bulldozing, transition and sliding. The friction coefficient decreased as the movement mode changed from static to sliding. The statistical analysis of the friction coefficient values showed that the mean value generally decreased with an increase in velocity. The static friction values were approximately the same for each test. The results of these tests will be presented in this paper, as well as a discussion of the implications of the results on the ride-up processes of ice on these types of shorelines.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.274
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.013
GPT teacher head0.257
Teacher spread0.244 · 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.

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

Citations0
Published2003
Admission routes2
Has abstractyes

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