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Record W2164696606 · doi:10.1139/h06-039

Energy expenditure while performing gymnastic-like motion in spacelab during spaceflight: case study

2006· article· en· W2164696606 on OpenAlexvenueno aff
Masahiro Kaneko, Kazuki Miyatsuji, Satoru Tanabe

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2006
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsnot available
FundersWaseda University
KeywordsSpaceflightMechanical energySpacecraftWork (physics)WeightlessnessEnergy expenditureInertiaSimulationPhysicsPower (physics)AeronauticsAerospace engineeringEngineeringMechanical engineeringMedicineClassical mechanics

Abstract

fetched live from OpenAlex

To estimate energy cost of a gymnastic-like exercise performed by an astronaut during spaceflight (cosmic exercise), energy expenditure was determined by measuring mechanical work done around the center of mass (COM) of the body. The cosmic exercise, which consisted of whole-body flexion and extension, was performed during a spaceflight and recorded with a video camera. By analyzing the videotape, the internal mechanical work (W(int)) against inertia load of the body segments was calculated. To compare how human muscles work on Earth, a motion similar to the cosmic exercise was performed by a control subject who had a physique similar to that of the astronaut. The total mechanical power of the astronaut was determined to be about 119 W; although the control subject showed a similar total power value, half of the power was external work (W(ext)) against gravitational load. By assuming a mechanical efficiency of 0.25, the energy expenditure was estimated to be 476 W or 7.7 W/kg, which is equivalent to that expended during fast walking and half of that used during moderate-speed running. Our results suggest that this form of cosmic exercise is appropriate for astronauts in space and can be performed safely, as there are no COM shifts while floating in a spacecraft and no vibratory disturbance.

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 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 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 score0.879
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.235
Teacher spread0.227 · 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 teacher head, not a consensus.

Study designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

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