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Record W2482422384 · doi:10.1117/3.1000981.ch5

Satellite Data Formatting and Packetization

2013· book-chapter· en· W2482422384 on OpenAlexaff
Shen‐En Qian

Bibliographic record

VenueSociety of Photo-Optical Instrumentation Engineers eBooks · 2013
Typebook-chapter
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsMetadataDisk formattingHousekeepingComputer scienceSpacecraftData systemInternational Space StationWorld Wide WebDatabaseEngineering

Abstract

fetched live from OpenAlex

Satellite instruments generate scientific data and associated engineering, housekeeping, and other metadata aboard spacecraft. This data needs to be transmitted reliably and transparently to users located in space or on Earth, which creates a need to format, parse into packets, and transmit space-acquired data from source to user in a standardized and highly automated manner. The Consultative Committee for Space Data Systems (CCSDS) is an international organization formed by the space agencies of the world to recommend and develop international standards for spacecraft data and information systems. As a subcommittee of the International Organization of Standards (ISO), the CCSDS has developed international standards for the transmission of space-acquired data from source to users to ease the transition toward greater automation within individual space agencies and to ensure harmony among the agencies, thereby resulting in greater cooperative opportunities and services.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.866
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.031
GPT teacher head0.238
Teacher spread0.208 · 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 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
Published2013
Admission routes1
Has abstractyes

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