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Record W4231632819 · doi:10.32920/ryerson.14656296

Characterization of noise in the lightning current derivative signals measured at the CN tower

2021· preprint· en· W4231632819 on OpenAlexaff
P. Liatos

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicRadio Wave Propagation Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTowerLightning (connector)Noise (video)Interference (communication)SIGNAL (programming language)Electrical engineeringCurrent (fluid)Lightning strikeAcousticsDerivative (finance)Electromagnetic interferenceMeteorologyComputer sciencePhysicsEngineeringTelecommunicationsLightning arresterStructural engineering

Abstract

fetched live from OpenAlex

Simultaneous measurements of parameters of CN Tower lightning strikes have been performed since 1991. The current derivative signals measured, are corrupted by a 100 kHz oscillating interference. This noise has caused substantial limitations on the usage of the CN Tower lightning current data. As a result, we became motivated to characterize it and search for its source. Furthermore identifying the low-frequency noise is expected to help in its removal and avoid it altogether in future installations. This thesis proves that the low-frequency noise corrupting the lightning current derivative signals is the Loran-C radionavigation signal. This finding is a major contribution not only for the CN Tower lightning project but also for any other research related to measurement of lightning at tall structures. Researchers and experimentalists should be aware of the existence of the Loran-C signal and take the necessary precautions to avoid its interference effect.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.038
GPT teacher head0.256
Teacher spread0.218 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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