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A Canadian Perspective on Arctic and Polar Over-the-Horizon Radar

2022· article· en· W4229365476 on OpenAlexaboutno aff
R. J. Riddolls

Bibliographic record

Venue2022 IEEE Radar Conference (RadarConf22) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAzimuthClutterOver-the-horizon radarRadarPolarThe arcticArcticRemote sensingComputer scienceGeologySituatedRadar trackerTelecommunicationsArtificial intelligencePhysicsOpticsAstronomyOceanography

Abstract

fetched live from OpenAlex

Two classes of Canada-specific Over-the-Horizon Radar (OTHR) systems are defined. Arctic OTHR (A-OTHR) systems are situated outside the auroral oval but perform some of their azimuthal scan in the direction of the oval. Clutter from ionospheric irregularities associated with the aurora must be suppressed over a finite azimuth extent, which can be done with a planar receive array that is either regularly sparse or oversampled sparse. Polar OTHR (P-OTHR) systems are situated inside the polar cap, and must suppress clutter from all azimuth angles. Auroral clutter control in P-OTHR systems requires a planar array that is either oversampled sparse or fully sampled.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.048
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0050.004
Scholarly communication0.0060.003
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0100.002

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 head0.216
Teacher spread0.210 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations7
Published2022
Admission routes1
Has abstractyes

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