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Record W1540112820 · doi:10.4271/2007-01-3286

The Effect of Wing Leading Edge Contamination on the Stall Characteristics of Aircraft

2007· article· en· W1540112820 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

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2007
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsBombardier (Canada)
FundersVolvo Research and Educational Foundations
KeywordsStall (fluid mechanics)WingAerospace engineeringLeading edgeAeronauticsContaminationEnvironmental scienceEnhanced Data Rates for GSM EvolutionComputer scienceEngineeringTelecommunicationsBiology

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">Lessons learned from analysis of in-service icing incidents are described. The airfoil and wing design factors that define an aircraft's natural stall characteristics are explored, including the aerodynamic effects of contamination. Special attention is given to contamination in the form of “roughness” along wing leading edges typical of frost. In addition, the key aerodynamic effects of ground proximity and sideslip/crosswind during the take-off rotation are described. An empirical method, that can be used to predict a wing's sensitivity to wing leading edge roughness, is demonstrated.</div> <div class="htmlview paragraph">The paper explores the in-service differences of aircraft that incorporate “hard”, “supercritical” and “slatted” wings. The paper attempts to explain why the statistical evidence appears to favor the slatted wing for winter operations.</div>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.006
GPT teacher head0.225
Teacher spread0.219 · 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