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Record W2811066011 · doi:10.14288/1.0314301

Combined tailings and mine waste

2017· article· en· W2811066011 on OpenAlexaff
Bryan Ulrich, Jeff Coffin

Bibliographic record

VenuecIRcle (University of British Columbia) · 2017
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTailingsWaste managementEnvironmental scienceHazardous wasteMining engineeringGeologyEngineeringMetallurgy

Abstract

fetched live from OpenAlex

The benefits of combining tailings and mine waste in a relatively homogenous manner, in which tailings just fill the voids between the waste rock particles while the waste rock maintains particle-to-particle contact, has been the subject of study over the course of several years. Such a combination of materials could be used for a closure cover or as a singular large-scale facility to store both mine waste products. The possible benefits of this combination of materials include the creation of a deposit with the footprint smaller than two dedicated facilities, the shear strength of waste rock, the permeability of tailings, low oxygen diffusion rates, and theoretically a decreased potential to develop and emit acid rock drainage. If properly combined and placed, such a landform may be constructible with steep stacking angles, and it may exhibit a low potential for liquefaction. The authors briefly discuss previous work by others and provide information regarding some recently completed advances in this methodology.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.938
Threshold uncertainty score0.985

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 head0.152
Teacher spread0.144 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

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