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Record W6948130797 · doi:10.48550/arxiv.1006.5256

Software systems for operation, control, and monitoring of the EBEX instrument

2010· preprint· en· W6948130797 on OpenAlexaff

Bibliographic record

VenuearXiv (Cornell University) · 2010
Typepreprint
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsMcGill University
Fundersnot available
KeywordsHousekeepingSoftwareCommand and controlInstrument controlVariety (cybernetics)Data acquisitionComponent-based software engineeringThe InternetTroubleshooting

Abstract

fetched live from OpenAlex

We present the hardware and software systems implementing autonomous operation, distributed real-time monitoring, and control for the EBEX instrument. EBEX is a NASA-funded balloon-borne microwave polarimeter designed for a 14 day Antarctic flight that circumnavigates the pole. To meet its science goals the EBEX instrument autonomously executes several tasks in parallel: it collects attitude data and maintains pointing control in order to adhere to an observing schedule; tunes and operates up to 1920 TES bolometers and 120 SQUID amplifiers controlled by as many as 30 embedded computers; coordinates and dispatches jobs across an onboard computer network to manage this detector readout system; logs over 3~GiB/hour of science and housekeeping data to an onboard disk storage array; responds to a variety of commands and exogenous events; and downlinks multiple heterogeneous data streams representing a selected subset of the total logged data. Most of the systems implementing these functions have been tested during a recent engineering flight of the payload, and have proven to meet the target requirements. The EBEX ground segment couples uplink and downlink hardware to a client-server software stack, enabling real-time monitoring and command responsibility to be distributed across the public internet or other standard computer networks. Using the emerging dirfile standard as a uniform intermediate data format, a variety of front end programs provide access to different components and views of the downlinked data products. This distributed architecture was demonstrated operating across multiple widely dispersed sites prior to and during the EBEX engineering flight.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.011

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 head0.062
GPT teacher head0.185
Teacher spread0.124 · 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 designNot applicable
Domainnot available
GenreSoftware

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
Published2010
Admission routes1
Has abstractyes

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