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Record W2372354105

Analysis on Fault Trips Caused by Forest Fire in CSG in the First Quarter of Year 2010

2011· article· en· W2372354105 on OpenAlexaboutno aff
Shu Shuang-yan

Bibliographic record

VenueGuangdong Electric Power · 2011
Typearticle
Languageen
FieldEngineering
TopicPower Systems and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsTRIPS architectureFault (geology)EngineeringElectric power transmissionQuarter (Canadian coin)Line (geometry)Transmission lineForensic engineeringTransport engineeringElectrical engineeringGeographySeismologyGeologyMathematics
DOInot available

Abstract

fetched live from OpenAlex

The fault trips on 220kV and above transmission lines caused by forest fire in CSG in the first quarter of year 2010,the corresponding protections and the impact on power transmission corridor are gathered and analyzed in terms of voltage levels of lines,failure time distribution,fault phase distribution,success rate of line reclosing,fault continuity and locality,etc.It is indicated that the forest fire can easily cause successive trips on several lines of the same line corridor and repeated trips on the same line in a short time.It is proposed that lines with fiber channels must be equipped with at least one current differential protection.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
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 head0.010
GPT teacher head0.191
Teacher spread0.182 · 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
Published2011
Admission routes1
Has abstractyes

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