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Record W4206908732 · doi:10.52321/igh.34.1.7

Use of geothermal energy and mineral waters in Bulgaria: current status and perspectives

2020· article· en· W4206908732 on OpenAlexaboutno aff
Vladimir Hristov

Bibliographic record

VenueEngineering Geology and Hydrogeology · 2020
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
FundersBulgarian National Science Fund
KeywordsGeothermal gradientHydrogeologyGeothermal energyGeological surveyCurrent (fluid)Mineral resource classificationGeologyMineral waterHydrothermal circulationEnvironmental scienceWater resource managementMining engineeringEarth scienceGeochemistryGeographyArchaeologyOceanographyGeophysicsGeotechnical engineering

Abstract

fetched live from OpenAlex

Summary data on the geological survey, hydrogeological and hydrochemical conditions, as well as on the use of geothermal energy and mineral waters during different periods in Bulgaria are presented. One of the aims of the paper is to present some problems concerning more rational and full application of the available geothermal resources, as well as the management of the existing geothermal resources to protect mineral water from contamination. Some examples are given from other countries (Austria, Russia) with similar hydrogeological conditions in the respective sites, which have smaller hydrothermal resources but use them more fully in the presented cases. Finally, brief information is provided on a new environmental technology for the use of geothermal energy, developed by the Canadian company “Eavor”. This technology could be applied in the near future in a number of areas in Central North and Northwestern Bulgaria where geological conditions are similar.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.079
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.222
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2020
Admission routes1
Has abstractyes

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