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Record W2020133605 · doi:10.1109/sipda.2011.6088431

CN tower lightning flash components

2011· article· en· W2020133605 on OpenAlexaff
A.M. Hussein, Monika Milewski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFlash (photography)Environmental scienceMeteorologyPhysicsOptics

Abstract

fetched live from OpenAlex

Based on the records of the new Phantom v5.0 high-speed imaging system (NHSIS) during the past five years (2006- 2010), the cumulative probability distributions of important CN Tower lightning flash parameters flash and ICC durations, flash multiplicity and inter-stroke time (1ST) were determined. During the reporting period, NHSIS recorded 68 CN Tower lightning flashes, of which 56 contained ICCs and 12 contained only return strokes. The flash multiplicity for all flashes (including 21 flashes that contain no return strokes), 35 flashes with ICCs and return strokes, and 12 flashes that contain only return strokes are, respectively, 2.19, 3.43, and 2.42. Therefore, the flash multiplicity of flashes having ICCs and return strokes is the highest. The cumulative probability distribution of ICC duration demonstrates that flashes with only ICCs have considerably larger ICC durations than those of flashes having ICCs and return strokes. Also, generally, flashes that have only return strokes have substantially higher inter-stroke time than that for flashes containing ICCs.

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)0.002
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 score0.985
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.027
GPT teacher head0.195
Teacher spread0.167 · 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

Citations7
Published2011
Admission routes1
Has abstractyes

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