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Record W2095978179 · doi:10.1109/tpwrs.2005.856992

An Aggregate Weibull Approach for Modeling Short-Term System Generating Capacity

2005· article· en· W2095978179 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Power Systems · 2005
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsWestern University
Fundersnot available
KeywordsSpot contractElectricityElectricity marketWeibull distributionElectric power systemDeregulationReliability (semiconductor)EconomicsTerm (time)Reliability engineeringElectricity price forecastingAggregate (composite)Computer scienceEconometricsEngineeringPower (physics)FinanceMacroeconomicsFutures contractElectrical engineering

Abstract

fetched live from OpenAlex

Deregulation of electricity markets is occurring all over the world. This trend introduces new risks and uncertainties into the electricity industry, the most significant being price risk. The spot price of electricity is highly volatile, and the ability to price risk management contracts on this commodity is contingent on a robust and realistic model of the underlying price process. One key driver of electricity spot price is the forced outages of generating plants in the system. The current paper describes a system aggregate model of short-term generating capacity that can be adapted to any generating system of interest. After describing the model, we test it using the IEEE Reliability Test System (RTS).

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.224
Teacher spread0.201 · 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