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Record W1976073361 · doi:10.4236/ojg.2014.45017

A Compilation of the Geo-Mechanical Properties of Rocks in Southern Ontario and the Neighbouring Regions

2014· article· en· W1976073361 on OpenAlexaffabout
Hayder Mohammed Salim Al-Maamori, M. Hesham El Naggar, S. Micic

Bibliographic record

VenueOpen Journal of Geology · 2014
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsWestern University
Fundersnot available
KeywordsGeologyDrillingDeformation (meteorology)Geotechnical engineeringMineralogyMining engineering

Abstract

fetched live from OpenAlex

The available measurements of the geo-mechanical properties of rocks in Southern Ontario and the neighbouring regions (New York, Ohio, Michigan, Indiana, Illinois, Wisconsin, and Minnesota) are summarized and presented. These measurements were compiled from available published data in the relevant literature and also from data that were collected from major underground projects in these regions. The compiled data are presented in three categories: measured in-situ stresses in different rock formations; calculated strength, stiffness and deformation including time-dependent deformation properties; and the measured dynamic properties of intact rock specimens from different rock formations in Southern Ontario and the neighbouring regions. The data presented in this paper can be used as a resource for preliminary evaluation of the geomechanical properties of the rocks in these regions. The presented geo-mechanical properties were generally obtained from in-situ measurements and from laboratory tests that were conducted on intact rock specimens from freshly excavated rock samples. Moreover, the time-dependent deformation properties of rocks in these regions were obtained from laboratory tests that were performed on intact rock specimens submerged in water. However, the influence of drilling fluids such as bentonite slurry and synthetic polymers solution, on the geo-mechanical properties of rocks is not evident and needs to 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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.575

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 head0.020
GPT teacher head0.201
Teacher spread0.181 · 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
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

Citations4
Published2014
Admission routes2
Has abstractyes

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