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Record W3112084114 · doi:10.1002/9781119181002.ch1

Introduction to Geothermal Energy

2016· other· en· W3112084114 on OpenAlex
Marc A. Rosen, Seama Koohi‐Fayegh

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

VenueGeothermal Energy · 2016
Typeother
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsScope (computer science)Geothermal gradientGeothermal energyKey (lock)SustainabilityEnergy (signal processing)Range (aeronautics)EngineeringComputer scienceEnvironmental scienceSystems engineeringGeologyPhysicsComputer securityGeophysicsEcologyAerospace engineering

Abstract

fetched live from OpenAlex

An introduction is provided to geothermal energy as a source of energy and technologies that can harvest it. Some key features of geothermal energy systems, such as its renewability and sustainability, as well as some of its advantages are briefly described. The main components of such systems are reviewed. The aim of this chapter is to provide the reader with basic information to help develop an understanding of the overall scope and range of material that is included in this book.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.393
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0850.008

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 head0.007
GPT teacher head0.213
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