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Record W4233925132 · doi:10.1002/9781119181002.ch5

Geothermal Heating and Cooling

2016· other· en· W4233925132 on OpenAlexaff
Marc A. Rosen, Seama Koohi‐Fayegh

Bibliographic record

VenueGeothermal Energy · 2016
Typeother
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsGeothermal heatingGeothermal gradientGeothermal energyHeat exchangerRenewable heatPetroleum engineeringEnvironmental scienceHeating systemElectricityPassive coolingHeat transferNuclear engineeringHeat pumpGeologyMechanicsMechanical engineeringEngineeringGeophysicsHybrid heatPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

Geothermal heating and cooling is the focus of this chapter. Ground-based energy can provide heating in winter and cooling in summer, in partial or full manners. Ground-source heat pumps normally form the basis of such systems and therefore are extensively discussed. Emphasis is placed on geothermal heat exchangers (also called ground, underground and ground-coupled heat exchangers), since they facilitate the exchange of heat between a fluid and the ground. For completeness, high-temperature geothermal systems are also described, including systems that essentially use the ground as a heat source for electricity generation and heating.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.074
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0740.027

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 head0.009
GPT teacher head0.224
Teacher spread0.214 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2016
Admission routes1
Has abstractyes

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