MétaCan
Menu
Back to cohort
Record W1993219991 · doi:10.2478/sgm031201

Description of hydraulic and strength properties of anisotropic geomaterials

2012· article· en· W1993219991 on OpenAlexaff
S. Pietruszczak, G. N. Pande

Bibliographic record

VenueStudia Geotechnica et Mechanica · 2012
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAnisotropyPermeability (electromagnetism)Porous mediumGeneralizationPorosityGeotechnical engineeringDarcy's lawMaterials scienceGeologyMechanicsMathematicsMathematical analysisPhysicsChemistryOptics

Abstract

fetched live from OpenAlex

Abstract In this paper, a simple generalization of Darcy’s law is proposed for the description of hydraulic properties of anisotropic porous materials. The coefficient of permeability is defined as a scalarvalued function of orientation. The principal directions of permeability are determined from a fabric descriptor specifying the distribution of average pore size. An example is provided for identification of material parameters, which is based on an idealized “pipe network model”. A procedure for defining the anisotropy in strength properties, which incorporates a conceptually similar approach, is also reviewed and an illustrative example is provided.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.223
Teacher spread0.203 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueStudia Geotechnica et MechanicaSame topicEnhanced Oil Recovery TechniquesFrench-language works237,207