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Record W2889674466 · doi:10.1109/lgrs.2018.2856185

High-Frequency Over-the-Horizon Radar in Canada

2018· article· en· W2889674466 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIEEE Geoscience and Remote Sensing Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsQueen's UniversityUniversity of WaterlooDefence Research and Development Canada
Fundersnot available
KeywordsOver-the-horizon radarRadarRadar trackerRay tracing (physics)Remote sensingComputer scienceFire-control radarSkywaveIonosphere3D radarTracking (education)Range (aeronautics)Radar engineering detailsGeologyRadar imagingTelecommunicationsAerospace engineeringGeophysicsEngineeringPhysicsOptics

Abstract

fetched live from OpenAlex

Over-the-horizon radars (OTHRs) have recently been making a comeback in Canada. As the need for accurate long-range tracking becomes more important, less-expensive ground-based radars are once again being considered for more effective long-range surveillance of Canadian airspace. Ray tracing is a powerful tool and is, especially, useful in applications requiring a detailed knowledge of radio wave propagation through the ionosphere. In this letter, new methods are developed to determine the feasible radar parameters such as operating frequencies, elevation angles, and absorption for OTHR operation using a 3-D ray tracing technique and up-to-date ionospheric, magnetic, and absorption models. The results of these simulations can be used for frequency monitoring systems and other OTHR applications in Canada.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.932
Threshold uncertainty score0.422

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 head0.004
GPT teacher head0.190
Teacher spread0.186 · 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