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Record W10306562

Inferred Weak Rock Mass Classification for Stope Design

2013· article· en· W10306562 on OpenAlexaboutno aff
Karina Forster

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsnot available
Fundersnot available
KeywordsRock mass classificationRock mass ratingGeologyLithologyMining engineeringStopingRock mechanicsGeotechnical engineeringPetrology
DOInot available

Abstract

fetched live from OpenAlex

Empirical design methods are commonly used for rock mechanics evaluations. An appropriate method of rock mass classification is required to use these empirical methods. There are limitations for rock mass classification methods when access to the ore zone is restricted. The Cameco Corporation Eagle Point Mine in northern Saskatchewan, Canada, uses the longhole open stope mining method for the recovery of uranium ore. The Modified Dilution graph is used for the prediction of stope hanging wall dilution. The mine currently uses a rock mass classification based on an estimate of the alteration and strength of a rock mass from geological drift mapping. Since this method is highly subjective, point load testing of diamond drill hole core was completed to attempt to correlate the alteration and strength of different rock types to remove the user subjectivity. The results of the testing indicated a general trend of decreasing rock strength with increasing alteration, albeit with considerable scatter. A repeatable, standardized method of evaluating the stope geometry and inferred rock mass classification for reconciliation purposes was developed. The standardized stope evaluation method removes significant subjectivity currently involved in estimates of stope geometries and the magnitude of dilution. A new lithology based method for interpreting the mine specific geological alteration and strength classification system was developed based on several sources of rock mass classification observations. This resulted in a correlation linking individual rock mass property descriptions between different classification systems for an improved estimate of the Q’ classification value. This improved method of estimating the rock classification Q’ value, as well as conventional techniques for linking classification systems, was used in a stope reconciliation process to predict open stope dilution. Twenty-seven stope reconciliation case histories were documented and used to compare predicted and measured dilution, based on three different approaches for estimating rock mass classification values. The results showed a minor improvement in dilution prediction using the approach developed in this study. The systematic stope reconciliation and rock mass classification approach did highlight areas in the weak pegmatoidal rocks where improved rock classification estimates should be investigated.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.285

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 science0.0000.000
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 head0.050
GPT teacher head0.241
Teacher spread0.191 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2013
Admission routes1
Has abstractyes

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