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Record W2911038031 · doi:10.1177/1754337118821575

Null effect of scratches made by curling rocks

2019· article· en· W2911038031 on OpenAlexafffund
Mark R. A. Shegelski, Edward P. Lozowski

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part P Journal of Sports Engineering and Technology · 2019
Typearticle
Languageen
FieldMedicine
TopicWinter Sports Injuries and Performance
Canadian institutionsUniversity of AlbertaUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Northern British Columbia
KeywordsCurlingGeologyCurl (programming language)Deflection (physics)MineralogyGeometryOpticsComposite materialPhysicsMathematicsMaterials science

Abstract

fetched live from OpenAlex

There is disagreement in the literature as to whether scratches made by curling rocks affect the motion of subsequent curling rocks. The aim of this investigation is to provide unequivocal experimental evidence to resolve this disagreement. Such evidence has been obtained by comparing the curl distances (total lateral deflections) of rocks sliding over ice with no scratches to curl distances of rocks sliding over ice completely covered with scratches made by previous curling rocks. The result of this simple experiment is that there is no appreciable difference in the curl distances between the two ice conditions. The conclusion is that the scratches made by curling rocks do not affect the motion of other curling rocks and that the lateral deflection of curling rocks cannot solely be due to scratches made by curling rocks.

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)0.003
metaresearch head score (Gemma)0.016
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.002
GPT teacher head0.191
Teacher spread0.189 · 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

Citations11
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part P Journal of Sports Engineering and TechnologySame topicWinter Sports Injuries and PerformanceFrench-language works237,207