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Record W1989203780 · doi:10.1139/t00-046

The CANLEX project: summary and conclusions

2000· article· en· W1989203780 on OpenAlexvenueaboutno aff
P. K. Robertson, C E Wride, Beth List, Upul Atukorala, Kevin W. Biggar, Peter Byrne, R. G. Campanella, D C Cathro, Dave Chan, K Czajewski, Wdl Finn, W. H. Gu, Yousef Hammamji, Bodo Hofmann, John A. Howie, J Hughes, Alan S. Imrie, J.‐M. Konrad, A. Küpper, T. C. Michael Law, E. R. F. Lord, P A Monahan, N. R. Morgenstern, Ryan Phillips, R Piché, H D Plewes, Donald A. Scott, David C. Sego, John Sobkowicz, Raymond A. Stewart, Bryan D. Watts, D J Woeller, T. Leslie Youd, Z Zavodni

Bibliographic record

VenueCanadian Geotechnical Journal · 2000
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsLiquefactionGeotechnical engineeringSoil liquefactionFlow (mathematics)StiffnessGeologySofteningEngineeringCivil engineeringMathematicsStructural engineering

Abstract

fetched live from OpenAlex

The Canadian geotechnical engineering community has completed a major collaborative 5 year research project entitled the Canadian Liquefaction Experiment (CANLEX). The main objective of the project was to study the phenomenon of soil liquefaction, which can occur in saturated sandy soils and is characterized by a large loss of strength or stiffness resulting in substantial deformations. The intent of this paper is to compare, interpret, and summarize the large amount of field and laboratory data obtained for six sites in Western Canada as part of the CANLEX project. The sites are compared in terms of both flow-liquefaction and cyclic-softening considerations. The paper presents a number of conclusions drawn from the project as a whole, in terms of both fundamental and practical significance.Key words: sand, flow liquefaction, cyclic softening, CANLEX.

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)0.007
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.879
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0030.001
Scholarly communication0.0060.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.003

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 head0.006
GPT teacher head0.187
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations58
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Soil MechanicsFrench-language works237,207