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Record W2607438370

A New Benchmark of Energy Performance for Energy Management in U.S. and Canadian Integrated Steel Plants

2017· article· en· W2607438370 on OpenAlexaboutno aff
Gale Boyd, M Doollin, Elizabeth Dutrow, S Zhang

Bibliographic record

VenueDukeSpace (Duke University) · 2017
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsnot available
Fundersnot available
KeywordsBenchmark (surveying)Energy (signal processing)EngineeringManufacturing engineeringEnvironmental scienceForensic engineeringEnvironmental economicsConstruction engineeringMechanical engineeringEconomicsGeographyMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

ENERGY STAR® supports businesses and consumers by making it easier to save money and protect the climate through superior energy efficiency. A key ENERGY STAR energy management tool for industry is the plant Energy Performance Indicator (EPI), which provides a bird’s-eye view of a plant’s sector-specific plant-level energy use via a functional relationship between the level of energy use and the level and type of various production activities, material input’s quality, and external factors. This paper describes the development of the first EPI for evaluating the energy performance of integrated steel mills in the U.S. and Canada.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.985

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 head0.006
GPT teacher head0.162
Teacher spread0.156 · 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 designTheoretical or conceptual
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

Citations4
Published2017
Admission routes1
Has abstractyes

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