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Record W2969254642 · doi:10.1080/15435075.2019.1650047

A comprehensive review of geothermal energy evolution and development

2019· review· en· W2969254642 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

VenueInternational Journal of Green Energy · 2019
Typereview
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRenewable energyProduction (economics)Greenhouse gasGeothermal energyFossil fuelEnvironmental economicsSustainable developmentGeothermal gradientSustainabilityEnergy developmentNatural resource economicsEmerging technologiesEnvironmental resource managementBusinessEngineeringEnvironmental scienceComputer scienceEconomicsWaste managementEcology

Abstract

fetched live from OpenAlex

Global energy demand is increasing, driven by population rise, technological development, and a desire for a better lifestyle. However, because environmental issues such as fossil-fuel-sourced greenhouse gas (GHG) emissions are emerging as constraints on the nature of energy sources, using renewable and sustainable energy sources is the appropriate and applicable response. Geothermal energy is one form of renewable and sustainable energy, which has certain advantages such as consistency, a vast amount of untapped potential, availability, and a wide range of possible applications that make it an interesting and viable solution for helping meet the world’s energy needs while reducing GHG emissions (especially CO2). We provide a comprehensive review on the evolution of geothermal energy production from its obscure beginnings to the present time by reporting production data from individual countries and collective data of worldwide production. In addition, we provide an overview of relevant technologies at the industrial level, such as site identification, power production methods, and direct use. Finally, we discuss the geothermal power production prospects for 2050, the classification of production capacity on the technology side, and existing roadmaps for points of interest concerning technological development. We hope this review helps to identify existing gaps, future challenges, and areas needing further attention and investigation.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.951
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.042
GPT teacher head0.302
Teacher spread0.261 · 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