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Record W2055827277 · doi:10.1117/12.405780

<title>Raven automated small telescope systems</title>

2000· article· en· W2055827277 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2000
Typearticle
Languageen
FieldEngineering
TopicAstronomical Observations and Instrumentation
Canadian institutionsnot available
Fundersnot available
KeywordsSatelliteNASA Deep Space NetworkChristian ministryComputer scienceSpace (punctuation)Remote sensingSystems engineeringSpace researchAerospace engineeringTelescopeMetric (unit)AeronauticsReal-time computingSpacecraftSimulationArtificial intelligenceEngineeringAstronomyPhysicsGeographyOperating system

Abstract

fetched live from OpenAlex

The Raven optical sensor is a commercial system being developed and tested by the Air Force Research Laboratory. It allows for a low cost method for obtaining high accuracy angular observations of space objects (manmade and celestial) with a standard deviation of approximately one arcsecond or less. Presented here is an overview of the past and present successes and future projects utilizing Raven. This system has evolved into a very viable and cost effective solution for obtaining low-cost observations for satellite and asteroid catalog and follow-up maintenance. Collaborative efforts between AFRL and several space agencies (JPL, NASA, Space Battlelab, Canadian Defense Ministry, etc) have successfully demonstrated and utilized the Raven system for their missions, including improved satellite orbit determination accuracy, NEO follow-ups, and remote autonomous collecting and reporting of metric data on deep space objects.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.594

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 science0.0000.000
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 head0.010
GPT teacher head0.205
Teacher spread0.195 · 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