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Sublevel retreat mining in the subarctic: a case study of the Diavik Diamond Mine

2018· article· en· W2897377775 on OpenAlex
Philip Lewis, Lyndon Clark, Steve Rowles, Chris Auld, Colline Petryshen, Aaron Elderkin

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
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsRio Tinto (Canada)
Fundersnot available
KeywordsSubarctic climateTundraMining engineeringDrillingGeologyUnderground mining (soft rock)Drilling and blastingStopingOpen-pit miningRock blastingCoal miningEngineeringArcticOceanographyWaste management

Abstract

fetched live from OpenAlex

Diavik Diamond Mine is located on the subarctic tundra of the Northwest Territories, Canada, 300 km northeast of Yellowknife. When its first two open pits were exhausted in 2012, it completed the full transition to underground mining. Three orebodies are currently being mined underground using two mining methods: blasthole open stoping and sublevel retreat (SLR). SLR was not an original method as described in the feasibility study. As the pits were mined, the underground project developed, and additional information became available. Over time, it became apparent that SLR would be the optimal method for two of the orebodies. A great deal has been learnt throughout development and operation of the SLR method at Diavik. This paper examines considerations for ventilation, production drilling and blasting, geotechnical concerns, and operational constraints for SLR mining in the subarctic. It also describes the process for method selection and the overall lessons learned.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.219
Teacher spread0.201 · 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