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Record W1626597280 · doi:10.1029/2004rs003123

Legendre coding for digital ionosondes

2005· article· en· W1626597280 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRadio Science · 2005
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLegendre polynomialsAmbiguity functionIonosondeAutocorrelationComputer scienceRadarAlgorithmPulse repetition frequencyAcousticsMathematicsTelecommunicationsWaveformPhysicsStatisticsMathematical analysis

Abstract

fetched live from OpenAlex

A 1019 bit Legendre code was evaluated for use in digital ionosondes. Experimental testing was done using the Canadian Advanced Digital Ionosonde (CADI). Theoretically, the 1019 Legendre code autocorrelation function of this new sequence has very low peak sidelobe level of −32.6 dB, and the system signal‐to‐noise‐ratio (SNR) will be improved by 30 dB compared with a single pulse code. Field experiments were done near London, Ontario, Canada, using two CADIs in a bistatic arrangement with 20 km spacing. The experimental results agreed with the theoretical estimation (with ∼1 dB error), but a 10 Hz frequency difference between the two computers' reference frequencies, which showed up as a Doppler shift in ambiguity function, necessitated additional signal processing to get optimal performance. The experimental measurements showed that the system was able to get ionospheric echoes with very low power transmission (1 W peak) at a quiet receiving site because of the high system SNR.

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 score0.562
Threshold uncertainty score0.203

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 communication0.0000.001
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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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