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Record W4382652998 · doi:10.1139/cgj-2023-0056

On the mechanics of filtered compacted consolidated and overconsolidated iron ore tailings at high pressures

2023· article· en· W4382652998 on OpenAlexaffvenue
João Paulo de Sousa Silva, João Vítor de Azambuja Carvalho, Alexia Cindy Wagner, Pedro Pazzoto Cacciari, Nilo César Consoli

Bibliographic record

VenueCanadian Geotechnical Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsPolytechnique Montréal
FundersUniversidade Federal do Rio Grande do SulConselho Nacional de Desenvolvimento Científico e TecnológicoMinisterio de Economía y CompetitividadCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsGeotechnical engineeringBreakageShearing (physics)Tailings damTailingsGeologyShear (geology)Materials scienceComposite materialMetallurgy

Abstract

fetched live from OpenAlex

The mechanics of filtered compacted normally consolidated (NC) and overconsolidated (OC) iron ore tailings (IOTs) was studied by performing triaxial testing at high pressures of up to 120 MPa. The OC specimens were obtained by isotropically compressing compacted IOT to 120 MPa, unloading it to distinct confining pressures, and shearing at constant radial stress. Particle size distribution analyses were used to examine the effect of compression and shear stresses on particle breakage. Additionally, the triaxial test results illustrate the stress history influence on the deviatoric stress–axial strain–volumetric strain curves, as well as on the IOT peak strength. Furthermore, these results also show that the amount of breakage during the shearing stage plays an essential role in the geomaterial’s response, marking the existence of curved critical state locus in both v–ln p′ and q– p′ planes, which is unique in the studied confined stress range (4–120 MPa) for the compacted NC and OC (considering OC ratio up to 30) IOTs.

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)0.000
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.191
Teacher spread0.180 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

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