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Record W2029657261 · doi:10.2478/humo-2013-0038

An assessment of hydrodynamic and simulated race performance features of three C-1 hull designs

2014· article· en· W2029657261 on OpenAlexaffabout
Michael G. Robinson, Laurence E. Holt, Thomas W. Pelham

Bibliographic record

VenueHuman Movement · 2014
Typearticle
Languageen
FieldEngineering
TopicShip Hydrodynamics and Maneuverability
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHullHumanitiesEngineeringArtMarine engineering

Abstract

fetched live from OpenAlex

Purpose Recently engineered Canadian Single (C-1) canoe hull designs have been found to produce less resistive drag than the traditional Delta design in tow tank test conditions. If these laboratory findings were found to be similar to on-water performance tests, then these new hull designs could give canoe sprint athletes a competitive advantage. However, these claims have not been independently confirmed nor has it been shown that these new designs result in improved performance under race conditions. Three C-1 hull designs (traditional Delta and the recently engineered Armageddon and Ergo-Starlight) were compared in order to detect differences in C-1 boat dynamics. Methods The C-1 canoes were propelled by eleven national- and international-class paddlers who performed 350-m all-out trials from a dead start in each of the three crafts. One-way ANOVA compared differences in means for individual 50-meter segment and 350-meter performance times. Results Performance times over the 350-meter race simulations were significantly faster (p = 0.038) among international-class paddlers with the Armageddon and Ergo-Starlight designs compared with the Delta. Conclusions International level canoeists should expect improved performance times by choosing the Armageddon and Ergo-Starlight versus the Delta-designed C-1.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.271
Teacher spread0.259 · 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 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
Published2014
Admission routes2
Has abstractyes

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