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Impact of skier actions on the gliding times in alpine skiing

2008· article· en· W1901788768 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScandinavian Journal of Medicine and Science in Sports · 2008
Typearticle
Languageen
FieldMedicine
TopicWinter Sports Injuries and Performance
Canadian institutionsUniversity of Calgary
FundersÖsterreichische ForschungsgemeinschaftChristian Doppler Forschungsgesellschaft
KeywordsDragSnowAlpine skiingAeronauticsEnvironmental scienceForensic engineeringPhysical medicine and rehabilitationMeteorologyEngineeringMedicineGeographyAerospace engineering

Abstract

fetched live from OpenAlex

Alpine ski races are typically won by fractions of a second. It is therefore essential for ski racers to minimize air drag as well as ski-snow friction. In contrast to air drag, ski-snow friction during actual skiing has rarely been investigated so far. Two tasks, forward/backward leaning and edging of the skis, were selected, which (a) were expected to have an impact on ski-snow friction, and (b) could be executed while gliding in tucked position. Two hypotheses were tested: (H1) Run times are affected by forward or backward leaning. (H2) Run times are affected by edging of the skis. Four professional ski testers were recruited, who conducted a total of 68 runs of straight gliding. Execution of the tasks was documented by video recordings and by measuring the force application point on the skis of one tester. The findings of this study support (H2) but not (H1). There are indications that the increased run times for edging are caused by increased ski-snow friction. From a performance point of view, it seems beneficial for ski racers to minimize edging in the gliding sections of a race.

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.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.043
GPT teacher head0.350
Teacher spread0.307 · 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