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Record W2156715305 · doi:10.1029/2005rs003347

Analysis of HF signal power observations on two North American circuits

2006· article· en· W2156715305 on OpenAlexaboutno aff
Leo F. McNamara, Richard J. Barton, T. Bullett

Bibliographic record

VenueRadio Science · 2006
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsnot available
Fundersnot available
KeywordsSunsetSunriseDecibelDaytimeSIGNAL (programming language)Electronic circuitPhysicsTelecommunicationsEnvironmental scienceElectrical engineeringAcousticsMeteorologyComputer scienceOpticsEngineeringAtmospheric sciences

Abstract

fetched live from OpenAlex

Observations of HF signal powers on two circuits in North America have been compared with the values predicted by two HF propagation programs, Voice of America Coverage Analysis Program (VOACAP) and Advanced Stand Alone Prediction System (ASAPS). Neither program consistently provided the more reliable predicted signal powers. For the longer circuit considered (2820 km WWV Fort Collins to Hanscom Air Force Base), ASAPS was found to be the more accurate program for the lower frequencies (at night), while VOACAP was the more accurate for the higher frequencies (during the day). The RMS errors ranged from a few decibels to 15 dB. For daytime 7.335 MHz propagation on the 490 km CHU Ottawa to Hanscom Air Force Base circuit, the VOACAP RMS errors (∼4 dB) were less than the ASAPS RMS errors (∼8 dB). The errors for the two programs were very similar for 3.330 MHz propagation, peaking at ∼9 dB just after sunrise and just before sunset and ∼3 dB during the night.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.228
Teacher spread0.214 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations9
Published2006
Admission routes1
Has abstractyes

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