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Record W2137854400 · doi:10.4271/2001-01-2099

Predicting Fatigue for Isolated Joints While Wearing an Extra-vehicular Mobility Unit (EMU)

2001· article· en· W2137854400 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 · 2001
Typearticle
Languageen
FieldEngineering
TopicSpace Exploration and Technology
Canadian institutionsLockheed Martin (Canada)
FundersNational Aeronautics and Space Administration
KeywordsUnit (ring theory)Computer scienceAutomotive engineeringEngineeringPsychology

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">To work outside a space craft, humans must wear a protective suit. The required suit pressurization creates additional resistance for the wearer while performing work. How much does the suit effect work and fatigue? To answer these questions, dynamic torque was collected for the shoulder, elbow and wrist for six subjects in an Extra-vehicular Mobility Unit (EMU). In order to quantify fatigue, the subjects were to exert maximum voluntary torque for five minutes or until their maximum fell below 50% of their initial maximum for three consecutive repetitions. Using the collected torque and time data, logarithmic based functions were derived to estimate torque decay to within an absolute error of 20%. These results will be used in the development of a generalized tool for prediction of maximum available torque over time for humans using the current EMU.</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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.032
GPT teacher head0.260
Teacher spread0.228 · 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