MétaCan
Menu
Back to cohort
Record W1949936154

신안풍력발전소 풍력터빈의 성능저하 분석

2013· article· ko· W1949936154 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venue태양에너지(한국태양에너지학회 논문집) · 2013
Typearticle
Languageko
FieldEngineering
TopicEngineering Applied Research
Canadian institutionsnot available
Fundersnot available
KeywordsWind powerNacelleEnvironmental scienceTurbineWind speedMeteorologyMarine engineeringEngineeringGeographyElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

This paper investigated wind turbine degradation quantitatively by analyzing the short-term operation records of the Shinan Wind Power Plant. Instead of a capacity factor which is needed to be normalized its variability due to monthly wind speed change, this study suggests an analysis method by taking the difference between the theoretical power output calculated from the nacelle wind speed and actual power output as the quantitative index of performance degradation. For three-year SCADA data analysis of the Shinan Wind Power Plant, it was confirmed that power output degradation rate of 0.54% per year. This value is within the average reduction rate 0.4%/year∼0.9%/year of normalized capacity factor of the onshore wind power plants in U.K. and Denmark; however, lower than the rate 2%/year of Canadian wind power plants.

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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.042

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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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