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Record W2534774326 · doi:10.1115/ipc2000-152

High Resolution Satellite Imagery: From Spies to Pipeline Management

2000· article· en· W2534774326 on OpenAlex
Steve Adam, Mike Farrell

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSatellite Image Processing and Photogrammetry
Canadian institutionsTransCanada (Canada)
Fundersnot available
KeywordsSatelliteRemote sensingLaunchedSatellite imageryPipeline (software)Space ShuttleComputer scienceHigh resolutionGeographyEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

In the past, high resolution satellite imagery was the domain of national security organizations. However, this has recently changed with the launch of Space Imaging’s IKONOS satellite. Launched on September 24, 1999 it is the world’s first commercial high resolution satellite, collecting data at 1-meter black/white and 4-meter multi-spectral. 2000 has the scheduled launch of at least two more commercial high resolution satellites. If these satellites are successfully launched, a buyer will be able to acquire imagery every day of the year (barring cloud cover). As an added convenience, an image user no longer has to buy a massive swath of imagery. For example, IKONOS scenes as narrow as 5km (3 miles) can be purchased. This development has opened the door for corridor applications and has been thoroughly and successfully implemented by TransCanada Pipelines in mapping over 1500km of their mainline.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.987
Threshold uncertainty score0.999

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)0.0020.002

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 head0.007
GPT teacher head0.208
Teacher spread0.201 · 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