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Record W1856166361 · doi:10.1139/cgj-2014-0149

Mechanical properties of a weak pyroclastic rock and their relationship with microstructure

2014· article· en· W1856166361 on OpenAlexvenueno aff
Paolo Tommasi, Luca Verrucci, T. Rotonda

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
FundersSapienza Università di Roma
KeywordsPyroclastic rockPozzolanaGeologyGeotechnical engineeringOedometer testPetrographyVolcanoMineralogyPozzolanGeochemistryMaterials scienceCementComposite material

Abstract

fetched live from OpenAlex

The geotechnical behaviour of very weak pyroclastic rocks controls both the failure mechanisms at the margins of rock mesas, where historic hill towns are often sited, as well as the stability of old underground cavities in urban areas of Central Italy. The study focuses on the mechanical behaviour of one of the pyroclastic materials forming the Orvieto mesa (pozzolana), not unlike other pozzolanas in Central and Southern Italy and other pyroclastites from volcanic districts worldwide. The mechanical properties under static conditions of this weakly cemented rock are reported. A petrographic and physical characterization of the material was preliminary conducted, followed by a wide range of mechanical tests: oedometer, uniaxial, and isotropic compression tests and indirect tensile tests. The stress–strain and strength behaviours of the pozzolana are highlighted and compared with those of the rock materials of the pyroclastic formation (tuff). The mechanical behaviour of the pozzolana is related to its physical and textural characters, with special reference to continuity of the groundmass and porosity. Finally, the role of the material behaviour at the field scale is discussed.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.362

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 integrity0.0000.001
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 head0.011
GPT teacher head0.165
Teacher spread0.155 · 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 designSimulation or modeling
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

Citations17
Published2014
Admission routes1
Has abstractyes

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