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Record W2633153788 · doi:10.18260/1-2--8406

The Geotechnical Virtual Laboratory

2020· article· en· W2633153788 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsConsolidation (business)EngineeringSession (web analytics)SoftwareCivil engineeringCurriculumComputer scienceGeotechnical engineeringWorld Wide Web

Abstract

fetched live from OpenAlex

The Geotechnical Virtual Laboratory is a computer based instructional package intended to complement, and potentially replace, some physical testing in a real geotechnical laboratory. The focus of this software is toward active learning and development of critical thinking skills, including data interpretation, understanding of the processes and influential factors, and problem solving. This paper is a progress report for a software development project, which has been underway at the University of Alberta since December 1998. A module on permeability testing has been completed and beta-tested, and another module on consolidation testing is in the final stage of development. The paper covers the initial design stages of the project (task analysis, initial concept, the teamwork management, etc.) and describes the outcomes from the permeability module and the results of its evaluation. It is clearly indicated by the students' feedback that a winning combination should include both a test simulation and experimental data sets, together with the data analysis tools. As well, it should address both theoretical and experimental aspects of a geotechnical problem, and enable their comparison.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.247

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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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

Quick stats

Citations4
Published2020
Admission routes2
Has abstractyes

Explore more

Same topicExperimental Learning in EngineeringFrench-language works237,207