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Comportamiento isotrópico a altas presiones de arenas de relave con finos no plásticos

2019· article· en· W3000760823 on OpenAlexaff
Camilo Espartaco Torres Córdova, Felipe Ochoa, Ramón Morillo‐Verdugo, Roberto Estrada Olguín, Miguel Bravo, Vicente Mercado

Bibliographic record

VenueObras y proyectos · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides Composition and Applications
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsPolitical scienceArt

Abstract

fetched live from OpenAlex

This article presents an experimental study that examines the isotropic triaxial behaviour of tailings sands in a wide range of pressures from 10 kPa to 5 MPa, varying the fine content of the tested samples. The results suggest that the presence and quantity of fines have influence in the behaviour: there is an increase in the compressibility of tailings sands deposited in a loose state, generating significant changes in the void ratio when confined throughout the range of pressures studied. In addition, it is observed that the effect of the fines in the compressibility decreases with the decrease of the void ratio, even exhibiting stiffening of the sample for the densest conditions of confection. Results of imaging performed post-test on the material suggest that the tailings sand exhibits a slight breakage of its angular edges when consolidated at high pressures. For low void ratios, differences in fines content of up to 4% are observed for clean sand. This difference decreases when the fine content of the sand increases, suggesting that the presence of fines contributes to the stability of the granular structure, redistributing the interparticle stresses, decreasing the level of breakage.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.208
Teacher spread0.199 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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