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Record W7037259474

The effect of pore solutions on the elastic modulus of rocks.

2002· dissertation· en· W7037259474 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2002
Typedissertation
Languageen
FieldComputer Science
TopicIntelligent Tutoring Systems and Adaptive Learning
Canadian institutionsnot available
Fundersnot available
KeywordsStress (linguistics)Elastic modulusYoung's modulusStress–strain curveModulusSaturation (graph theory)Compressive strength
DOInot available

Abstract

fetched live from OpenAlex

The objective of the research was to determine the effect of saturation and ionic solutions on the elastic modulus (Young's Modulus) of rocks. It is based on the testing of 78 samples, which are considered representative of rock formations in Southern Ontario. Initially a number of physical parameters were measured, including absorption, adsorption, porosity, unit weight and length change due to freezing. A uniaxial compressive stress frame was designed and built to facilitate the stress portion of the research program. Samples were subjected to varying levels of moisture, temperature and ionic conditions for a preset time period and immediately removed and put under stress. Stress and length change of the sample were recorded during the test. Young's Modulus was calculated from the stress and strain results. All the results (combined with additional results extracted from the same samples in previous studies by Stephen Rigbey, 1980 and Ivan Dananaj, 2001) were subjected to multivariate statistical analysis, which included correlation tests, cluster analysis, factor analysis, regression and t tests. (Abstract shortened by UMI.)Dept. of Earth Sciences. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2002 .P685. Source: Masters Abstracts International, Volume: 41-04, page: 1036. Adviser: Peter P. Hudec. Thesis (M.Sc.)--University of Windsor (Canada), 2002.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.214
Teacher spread0.195 · 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 designTheoretical or conceptual
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
Published2002
Admission routes1
Has abstractyes

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