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Record W2298870433 · doi:10.14288/1.0042341

Managing mine subsidence risks at the Three Sisters Resorts development in Canmore, Alberta

2009· article· en· W2298870433 on OpenAlexaffabout
Ray S. Predika, Richard Dawson, HG Stephenson

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldEngineering
TopicGeomechanics and Mining Engineering
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSubsidenceMining engineeringBusinessEnvironmental planningEnvironmental resource managementGeologyGeographyEnvironmental science

Abstract

fetched live from OpenAlex

This paper will discuss investigation methods, risk-based evaluation techniques, and remediation strategies that are employed to manage the hazards associated with shallow room and pillar coal mines. Key issues are the size of the development and its proximity to extensive mine workings, as well as the mitigation strategies that have been employed to remediate the mine workings for a wide range of ground conditions and land use objectives. Prior to development, areas are assessed using a risk matrix which correlates the proposed land use with the type of mining hazard that is present beneath the area in order to evaluate the necessity and extent of mitigation that is required. This provides a consistent framework that guides development for the property, and also provides a means with which to convey risk to the developer, investors, regulators, and the general public.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.672
Threshold uncertainty score0.659

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.162
Teacher spread0.151 · 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 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
Published2009
Admission routes2
Has abstractyes

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