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Record W3025766950

Risky business: Improving the mine reclamation regime in British Columbia

2020· article· en· W3025766950 on OpenAlexaboutno aff
Claudia Malinowski

Bibliographic record

VenueSummit (Simon Fraser University) · 2020
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsLand reclamationBusinessForensic engineeringMining engineeringEngineeringHistoryArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Mine reclamation is considered an integral part of mine closure and is imperative to the conservation of land, watersheds, and natural habitats.British Columbia was one of the first jurisdictions in Canada to adopt mine reclamation legislation and has since expanded its reclamation regime.However, the province has experienced some of the largest environmental mining disasters in Canada and continues to have insufficient safeguards to ensure sustainable mine closure.Several studies have explored financial assurance as a solution to this issue, but few have evaluated the benefits of preventative efforts adopted during the mine planning process.This study attempts to fill this gap by evaluating pollution prevention policies in other mining jurisdictions and identifying options to enhance reclamation outcomes in BC's mining industry.Three policy options are considered: prohibiting mines with perpetual water treatment, strengthening regulations on tailings storage facilities, and introducing a funding program aimed at mining innovation.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.389

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.158
Teacher spread0.150 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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