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Record W2326514069 · doi:10.2514/6.2001-4304

Measure of smoothness for motion actuator travel

2001· article· en· W2326514069 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

VenueAIAA Modeling and Simulation Technologies Conference and Exhibit · 2001
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsMeasure (data warehouse)SmoothnessActuatorMotion (physics)Computer scienceComputer visionArtificial intelligenceMathematicsMathematical analysisData mining

Abstract

fetched live from OpenAlex

The dynamics of an actuator is an important consideration in the design of a motion cueing system for pilot training. The dynamic properties include the quality of actuator travel, as well as its speed and force capabilities. An actuator with smooth motion supplies higher-fidelity cues than one that provides noticeably grainy motion. Motion smoothness is most often evaluated subjectively. However, an objective measurement of actuator smoothness is advantageous because it improves the consistency and precision of smoothness measurements. This results in increased confidence in system performance. This paper presents a method of measuring smoothness objectively on a dynamic seat motion simulator.

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)0.000
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 score0.943
Threshold uncertainty score0.374

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 head0.069
GPT teacher head0.328
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