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Record W2779340447 · doi:10.1139/cjes-2017-0186

Real-time monitoring for structural health, public safety, and risk management of mine tailings dams

2017· article· en· W2779340447 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2017
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsBC Innovation CouncilNational Research Council Canada
Fundersnot available
KeywordsTailingsWork (physics)StakeholderRisk analysis (engineering)Stakeholder engagementBusinessEnvironmental planningEngineeringEnvironmental economicsEnvironmental science

Abstract

fetched live from OpenAlex

Public awareness of tailings dam failures is increasing in the wake of incidents in Canada and abroad. The present work establishes the current state of practice in mine tailings dam monitoring and provides a summary of the current technical and operational gaps identified through industry and stakeholder engagement. These gaps may be addressed with currently available technologies supplied by commercial instrumentation manufacturers; however, the assumed costs and lack of regulatory demand may serve as barriers to adoption. An integrated approach and diverse suite of technologies is needed to address issues of dam stability, worker and public safety, and environmental protection. Technological applications and limitations are described and design requirements are proposed for an integrated, real-time monitoring system. Socio-economic impacts and loss reduction benefits are considered and the need for industry and regulator participation is emphasized.

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)0.001
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 score0.296
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.027
GPT teacher head0.251
Teacher spread0.224 · 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