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Record W3048445961 · doi:10.1201/9781003078555-20

Design of paste tailings disposal in the Russian Sub-Arctic

2020· book-chapter· en· W3048445961 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicEngineering and Environmental Studies
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsTailingsArcticEnvironmental scienceThe arcticWaste managementEarth scienceGeologyMining engineeringEngineeringOceanographyMetallurgyMaterials science

Abstract

fetched live from OpenAlex

The Julietta Gold Project is a proposed gold mine in the Magadan Province of eastern Russia. The project, a joint venture of Russian and Canadian interests, proposes to use paste for the surface tailings disposal system for the mine. The paste would be deposited on surface when it is not being used as backfill for the underground operation. Approximately 45% of the tailings would be used underground as paste backfill while the remainder would be disposed of on surface at a slurry density of approximately 75%. The use of the paste underground and on surface reduces the disposal area by over 75% compared to a conventional disposal facility and reduces the environmental impact at the site as the low moisture content of the tailings will allow them to freeze as placement proceeds. The economics of the underground operation are improved with the use of paste backfill and the economics on surface are improved with the smaller disposal area. This paper discusses the feasibility study for the surface disposal of the tailings.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.659

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 head0.012
GPT teacher head0.160
Teacher spread0.148 · 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

Quick stats

Citations1
Published2020
Admission routes2
Has abstractyes

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