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Record W2358620900

Generalized mixture rule and its applications to rheology of the Earth materials.

2006· article· en· W2358620900 on OpenAlexaff
Ji Shao

Bibliographic record

VenueActa Petrologica Sinica · 2006
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsRheologyCrustMantle (geology)GeologyPorosityPolyphase systemDeformation (meteorology)TectonicsMineralogyGeophysicsMechanicsMaterials scienceGeotechnical engineeringPhysicsComposite material
DOInot available

Abstract

fetched live from OpenAlex

Efforts to model the tectonic deformation behavior of the Earth's crust and mantle will become easier if a simple but robust expression is available to make accurate predictions of the elastic and rheological properties of candidate multiphase rocks under various conditions. For this intent, a generalized mixture rule (GMR) is established to provide a unified description of the mechanical properties of polyphase composites or polymineralic rocks in terms of component properties, volume fractions, and microstructures. Taking solid-liquid suspensions (e. g. , magmas) and porous materials (e. g. , basalts and sandstones) as end-members of two-phase composites in which solid particles or pores are dispersed within a continuous liquid or solid framework, the GMR yields a rigorous expression for the relationship between the mechanical properties and component volume fractions. Although the GMR is purely mathematical in origin, its connection to the existing physical theories and its consistence with extensive high-quality experimental data suggests that it should have some physical validity as a very handy tool for a general description of the elastic and rheological properties of multiphase materials including suspensions and porous solids. Rigorous theoretical analyses could be a very challenging topic.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.205
Teacher spread0.198 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

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