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Record W2157416082 · doi:10.1109/ptc.2003.1304750

Waveform parameters of fields generated by lightning strokes to the CN tower and to objects in its vicinity

2004· article· en· W2157416082 on OpenAlexaff
A.M. Hussein, W. Janischewskyj, Monika Milewski, V. Shostak, Jen-Shih Chang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsMcMaster UniversityUniversity of TorontoToronto Metropolitan University
Fundersnot available
KeywordsLightning (connector)WaveformTowerElectromagnetic pulseElectromagnetic interferenceLightning strikeElectric fieldElectromagnetic fieldPhysicsElectromagnetic compatibilityAcousticsEMIPulse (music)Electrical engineeringMeteorologyOpticsVoltageEngineeringStructural engineering

Abstract

fetched live from OpenAlex

Since 1991, broadband, high-resolution measurement systems have simultaneously captured the lightning current derivative at the CN tower and the corresponding lightning-generated electric and magnetic fields 2 km north of the tower. Extensive cumulative statistics of waveform parameters (peak, 10% to 90% risetime to peak and pulse width at the 50% level of the peak) of electric and magnetic field signals, generated by lightning return-strokes to the CN Tower during the past eleven years (1992-2002), have been derived and are presented in this paper. Furthermore, waveform parameters of electric fields radiated from lightning strikes to the CN Tower and to other objects in its vicinity are compared. It is shown that the risk from electromagnetic interference (EMI) due to the lightning-generated electromagnetic pulse (LEMP) is substantially elevated near a tall structure. The presented statistical results will assist in the establishment of more sophisticated protective measures against interference due to lightning-generated electromagnetic pulses, especially those generated from lightning occurring at tall structures.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.280

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 head0.007
GPT teacher head0.214
Teacher spread0.206 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations10
Published2004
Admission routes1
Has abstractyes

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