MétaCan
Menu
Back to cohort
Record W2001664122 · doi:10.3384/ecp09430037

Modelica Library for Improved Spacecraft Resource Budgeting

2009· article· en· W2001664122 on OpenAlexaff
Niccolo Cymbalist, Marc-Andre Lauriault, Chahé Adourian

Bibliographic record

VenueLinköping electronic conference proceedings · 2009
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsModelicaSpacecraftComputer scienceResource (disambiguation)Aerospace engineeringSystems engineeringSimulationEngineering

Abstract

fetched live from OpenAlex

The SpacecraftLib library has been developed in Modelica for use in the domain of Systems Engineering for space systems with a special emphasis on modularity, usability and ease of modification and expansion.It is a multidisciplinary tool which combines all the relevant subsystems.Power, command and data handling, and mechanical models are integrated into a single Modelica device in order to model as completely as possible the behaviour of a physical onboard device.We will describe the tool, examine a case study and briefly analyze the results of a simulation.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.100
Threshold uncertainty score0.336

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1000.030

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 head0.200
Teacher spread0.193 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueLinköping electronic conference proceedingsSame topicSpacecraft Design and TechnologyFrench-language works237,207