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Record W2626415203

Canadian Advanced Nanospace eXperiment 7 (CanX-7) Mission Analysis, Payload Design and Testing

2012· dissertation· en· W2626415203 on OpenAlexfundaboutno aff
Barbara Shmuel

Bibliographic record

VenueTSpace · 2012
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsPayload (computing)AeronauticsEngineeringAerospace engineeringSystems engineeringComputer scienceComputer security
DOInot available

Abstract

fetched live from OpenAlex

A deorbiting drag device is being designed and built by the University of Toronto Institute for Aerospace Studies/Space Flight Laboratory (UTIAS/SFL) to be demonstrated on the Canadian Advanced Nanospace eXperiment 7 (CanX-7) satellite. CanX-7 will address the growing issue of space debris by designing a drag sail device that will be demonstrated for cubesat-sized satellites. Mission analysis done to ensure the drag device functions properly and deorbits within the required lifetime is performed while varying different properties such as drag coefficient, effective drag area, and solar cycle variations. The design evolution of the device is documented and the chosen design, along with several stages of prototyping, is described. The individual components that make up the device are described as are preliminary numerical analyzes. Finally, the test plan required for the device is described with several deployment experiments and risk reduction tests documented.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.121
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.288
Teacher spread0.275 · 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 source (direct Gemma or distilled Codex), 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
Published2012
Admission routes2
Has abstractyes

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