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Record W4412459356 · doi:10.3847/2515-5172/aded09

Bioburden Reductions on the Europa Clipper Spacecraft During its MEGA-trajectory Cruise to Jupiter

2025· article· en· W4412459356 on OpenAlexaff
Ruella Ordinaria, John E. Moores, Grace Bischof, Andrew C. Schuerger

Bibliographic record

VenueResearch Notes of the AAS · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsYork University
Fundersnot available
KeywordsCruiseClipper (electronics)Jupiter (rocket family)BioburdenSpacecraftMega-JovianAerospace engineeringAeronauticsEnvironmental scienceAstrobiologyMeteorologyPlanetAstronomyEngineeringGeographyPhysicsElectrical engineeringMedicine

Abstract

fetched live from OpenAlex

Abstract The Cruise-Phase Microbial Survival (CPMS) model was used to estimate the bioburden reduction on the Europa Clipper (EC) spacecraft during its transit to Jupiter based on the final flown Mars–Earth gravity assist (MEGA) trajectory, a trajectory not considered in previous work. The CPMS model evaluates the bioburden reduction due to UV radiation, temperature, and vacuum. Under the MEGA trajectory, bioburdens on external and shallow interior surfaces accumulate the highest reductions due to the synergistic effects of temperature and vacuum, contributing to hundreds of thousands of Sterility Assurance Levels (SALs). Deep internal surfaces do not reach one SAL unless heated to at least 233 K. The revised CPMS model estimates that there will be no viable bioburden remaining on or near the exterior surfaces of the EC spacecraft upon its arrival at Jupiter following the completion of the MEGA trajectory.

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)0.001
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 score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0010.000

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 head0.093
GPT teacher head0.364
Teacher spread0.271 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueResearch Notes of the AASSame topicPlanetary Science and ExplorationFrench-language works237,207