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Record W2261494320 · doi:10.1109/mcom.2015.7105663

Testing a self-healing material in microgravity using a 3U cubesat

2015· article· en· W2261494320 on OpenAlexafffund
Mehdi Sabzalian, J. A. Whatley, Nathalie Parmentier, Ali Elawad

Bibliographic record

VenueIEEE Communications Magazine · 2015
Typearticle
Languageen
FieldMaterials Science
TopicSilicone and Siloxane Chemistry
Canadian institutionsConcordia University
FundersConcordia UniversityNational Aeronautics and Space Administration
KeywordsCubeSatPayload (computing)Computer scienceSatelliteSpace (punctuation)Space suitAerospace engineeringSelf-healingTest (biology)Space technologyPoint (geometry)AeronauticsSimulationSystems engineeringRemote sensingComputer securityEngineeringGeologyOperating system

Abstract

fetched live from OpenAlex

Space Concordia, a student society from Concordia University, has designed and built a 3U CubeSat named Aleksandr as their entry into the 2014 CSDC. The satellite, once deployed, will test the properties of a self-healing carbon composite by performing a three-point bending test in space, and thereby assess its viability for use in space applications. The engineering model of the satellite payload met all CSDC testing requirements and placed second in the competition. Space Concordia now aims to expand and refine Aleksandr to participate in the upcoming CSDC.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.106
GPT teacher head0.328
Teacher spread0.222 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2015
Admission routes2
Has abstractyes

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