MétaCan
Menu
← Back to cohort
Record W2078682685 · doi:10.2514/6.2011-3822

Characterization of the gaseous spacecraft environment of Rosetta by ROSINA

2011· article· en· W2078682685 on OpenAlexaff
Bernhard Schläppi, K. Altwegg, H. Balsiger, Ursina Calmonte, M. Hässig, Lukas Hofer, A. Jäckel, P. Wurz, B. Fiethe, M. Rubı́n, S. A. Fuselier, J. J. Berthelier, Johan De Keyser, H. Rème, U. Mall

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsLockheed Martin (Canada)
FundersCentre National d’Etudes SpatialesBelgian Federal Science Policy OfficeUniversity of MichiganNational Aeronautics and Space Administration
KeywordsSpacecraftAstrobiologyCharacterization (materials science)Computer scienceAerospace engineeringEnvironmental scienceEngineeringPhysicsMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

For critical optical surfaces and sensitive instrumentation, contamination due to spacecraft outgassing is a nuisance. To avoid or minimize the resulting, limiting factors in the future, a comprehensive understanding of the outgassing mechanisms is necessary. Here we summarize findings from outgassing studies using the Rosetta Orbiter Spectrometer for Ion and Neutral Analysis (ROSINA) on the Rosetta spacecraft. Data are available for a flight time of more than six years, a large range of heliocentric distances, and a variety of different test scenarios.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.001
Research integrity0.0000.000
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 head0.005
GPT teacher head0.158
Teacher spread0.153 · 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 designObservational
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

Citations5
Published2011
Admission routes1
Has abstractyes

Explore more

Same topicIonosphere and magnetosphere dynamics→French-language works237,207→