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Record W7081992917 · doi:10.36487/acg_repo/2515_64

A closure case study: the multidisciplinary and interconnected opportunities and challenges at a mine in northern Ontario, Canada

2025· article· en· W7081992917 on OpenAlexaboutno aff

Bibliographic record

VenueMine closure · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsClosure (psychology)Plan (archaeology)Multidisciplinary approachScope (computer science)Work (physics)TailingsLand reclamation

Abstract

fetched live from OpenAlex

This paper explores the challenges and opportunities of a mine’s closure plan amendment (CPA) in northern Ontario, Canada, which supports expanding the mine plan and extending the mine life. The future mine plan includes going underground, consolidating two neighbouring open pits, shifting and expanding a mine rock stockpile, and adding a fourth tailings facility. The scope of this closure plan is extensive and interconnected. There is the multidisciplinary nature of including all aspects of mine planning throughout its operational life, ultimate configurations and anticipating the needs to run a large mine, while also planning for reclamation and closure for what will be. There are over 15 technical studies that support the CPA. These studies are interconnected and result from one cascade into the next. Of the 15 studies, more than half are related to water, water balance, water quality, interaction of surface and groundwater, bioremediation, water management infrastructure, and impacts of water on land cover. More than six consultants support this work and all the mine’s departments came together to find alignment for two difficult challenges: more potentially acid generating waste than in the original mine plan and more water than previously modelled. The paper will walk through understanding how these scopes intertwine and the importance of working the interconnectivity and multidisciplinary nature of closure planning together to create a CPA.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.525

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 science0.0000.001
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 head0.042
GPT teacher head0.237
Teacher spread0.195 · 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
Published2025
Admission routes1
Has abstractyes

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