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Record W881196101 · doi:10.24084/repqj10.288

Strategies to Reduce the Use of Fossil Fuels

2017· article· en· W881196101 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

VenueRenewable Energy and Power Quality Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicBelt Conveyor Systems Engineering
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRenewable energyEnvironmental scienceEnergy (signal processing)Environmental economicsNatural resource economicsRemote sensingEngineeringGeologyElectrical engineeringEconomicsPhysics

Abstract

fetched live from OpenAlex

Mining industry is a substantial consumer of the energy indispensable to power mining and mineral processing equipment and processes. As more and more mine operations move to remote locations, the access to reliable, secure and environment friendly energy sources becomes a key concern. At present, a great majority of remote mines relies heavily on diesel fuel that has to be transported over long distances. In this context, some of the renewable energy sources such as for example wind power or solar energy seem to provide potentially interesting and viable alternatives. Mine operations however, have a very particular character, much different from other industries and from other potential applications of renewable power sources. This paper presents operational conditions of some mining operations, particularly those in remote regions, in the context of their energy needs. The authors analyse current and future capacities to decrease a reliance of remote mines on conventional fuels and energy. The paper analyses and discusses also the conditions to be met by alternative energy sources so that they might become a viable alternative for remote mining operations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.063
GPT teacher head0.284
Teacher spread0.221 · 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