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Record W4413115982 · doi:10.1007/s11214-025-01199-x

The Tandem Reconnection and Cusp Electrodynamics Reconnaissance Satellites (TRACERS) Science Operations Center

2025· article· en· W4413115982 on OpenAlexaff
I. W. Christopher, C. A. Kletzing, D. Crawford, Chris Piker, DL Wilkinson, Kim Steele, Steve Petrinec, S. R. Bounds, Steven Vaclavik, Saad Omar, E. O. Shul'Ts, Michael Winter, David M. Miles

Bibliographic record

VenueSpace Science Reviews · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsNexen (Canada)
FundersGoddard Space Flight CenterNational Aeronautics and Space Administration
KeywordsSpacecraftEphemerisSpace SciencePhysicsScientific instrumentCitizen scienceData processingRemote sensingComputer scienceSystems engineeringAerospace engineeringAstronomySatelliteDatabaseEngineeringGeography

Abstract

fetched live from OpenAlex

The primary purpose of the Tandem Reconnection And Cusp Electrodynamics Reconnaissance Satellites (TRACERS) Science Operations Center (SOC) is to ensure that the data necessary to achieve the TRACERS science goals are acquired, processed, and distributed to the scientific community. The SOC role in data acquisition is to facilitate science instrument planning and operations, through a weekly commanding cycle. Data processing includes generation of Level 0 and Level 1 data products, creation of Spacecraft Planet Instrument Camera-matrix Events (SPICE) kernels to provide spacecraft ephemerides and coordinate transforms for the mission, and ensuring consistency of all Level 2+ products produced by the individual instrument teams. Data distribution is undertaken in two ways. First, by hosting TRACERS data products on a public web portal during the active mission, and second by preparing mission data for transfer to the Space Physics Data Facility (SPDF) for long-term archiving.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.002
Scholarly communication0.0010.001
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 head0.009
GPT teacher head0.277
Teacher spread0.268 · 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.

Study designNot applicable
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

Citations2
Published2025
Admission routes1
Has abstractyes

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