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Record W2550338908 · doi:10.1017/cbo9781316543832

Thermo-Poroelasticity and Geomechanics

2016· book· en· W2550338908 on OpenAlexaff
A. P. S. Selvadurai, A. P. Suvorov

Bibliographic record

VenueCambridge University Press eBooks · 2016
Typebook
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsMcGill University
Fundersnot available
KeywordsGeomechanicsPoromechanicsBenchmark (surveying)Computer scienceResource (disambiguation)Management scienceData scienceConstruction engineeringEngineeringGeologyGeotechnical engineeringPorous medium

Abstract

fetched live from OpenAlex

Investigations of multi-physical processes in geomaterials have gained increasing attention due to the ongoing interest in solving complex geoenvironmental problems. This book provides a comprehensive exposition of the classical theory of thermo-poroelasticity, complemented by complete examples to problems in thermo-poromechanics that are used to validate computational results from multi-physics codes used in practice. The methodologies offer an insight into real-life problems related to modern environmental geosciences, including nuclear waste management, geologic sequestration of greenhouse gases to mitigate climate change, and the impact of energy resources recovery on groundwater resources. A strong focus is placed on analytical approaches to benchmark the accuracy of the computational approaches that are ultimately used in real-life problems. The extensive coverage of both theory and applications in thermo-poroelasticity and geomechanics provides a unified presentation of the topics, making this an accessible and invaluable resource for researchers, students or practitioners in the field.

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)0.001
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 score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0300.016

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 head0.008
GPT teacher head0.150
Teacher spread0.142 · 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

Citations88
Published2016
Admission routes1
Has abstractyes

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