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Record W2883244135

A Model of Ice Friction For an Inclined Incising Slider

2012· article· en· W2883244135 on OpenAlexaffvenue
Edward P. Lozowski, Krzysztof Szilder, Sean Maw

Bibliographic record

VenueNPARC · 2012
Typearticle
Languageen
FieldMedicine
TopicWinter Sports Injuries and Performance
Canadian institutionsMount Royal UniversityNational Research Council Canada
Fundersnot available
KeywordsSliderGeologyEngineeringMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

The FAST 2.0 model of ice friction was developed for a vertically oriented speed skate. The model is therefore left-right symmetrical about a vertical plane parallel to the sliding direction. It describes ice friction at sliding velocities sufficiently high to produce a lubricating layer of meltwater, which completely separates the ice and slider surfaces. Friction results from ploughing a groove in the ice and from the shear stress in the lubricating Couette flow. The model takes into account frictional melting, heat conduction into the ice and the lateral squeeze flow of the lubricating liquid. Here we present a new, numerical model, FAST 2.0i, which calculates ice friction for an inclined runner that is incising into the ice. Specifically, we consider an inclined speed skate blade and we use it to predict the variation of ice friction during a typical skating stroke. The model results compare favorably with in situ measurements. Copyright © 2012 by the International Society of Offshore and Polar Engineers (ISOPE).

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.064
GPT teacher head0.333
Teacher spread0.269 · 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 designSimulation or modeling
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
Published2012
Admission routes2
Has abstractyes

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