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Record W4236546981 · doi:10.1139/t00-045

Ground sampling program at the CANLEX test sites

2000· article· en· W4236546981 on OpenAlexfundvenueaboutno aff
C E Wride, Bodo Hofmann, David C. Sego, H D Plewes, J.‐M. Konrad, Kevin W. Biggar, P. K. Robertson, P A Monahan

Bibliographic record

VenueCanadian Geotechnical Journal · 2000
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of AlbertaSyncrude
KeywordsCoringSampling (signal processing)GeologyBoreholeGeotechnical engineeringWell loggingVoid ratioSonic loggingGroundwaterLiquefactionInclinometerCore samplePiezometerExcavationDrillingMining engineeringAquiferPetroleum engineeringEngineeringCore (optical fiber)

Abstract

fetched live from OpenAlex

One of the primary objectives of the Canadian Liquefaction Experiment (CANLEX) project was to develop and evaluate undisturbed sampling techniques as part of the overall goal to focus and coordinate Canadian geotechnical expertise on the topic of soil liquefaction. Six sites were selected by the CANLEX project in an attempt to characterize various deposits of loose sandy soil. The sites consisted of a variety of soil deposits, including hydraulically placed sand deposits associated with the oil sands industry, natural sand deposits in the Fraser River Delta, and hydraulically placed sand deposits associated with the hard-rock mining industry. At each site, a target zone was selected and various methods of ground sampling were performed. These included ground freezing and sampling, fixed piston tube sampling, Christensen double-tube core sampling, large-diameter sampling using the Laval sampler, and sonic (rotary-vibratory) continuous coring. Ground freezing and sampling was performed at all six sites; the other methods were used at only some sites. Geophysical (gamma-gamma) logging was also performed in boreholes near the freeze pipe to independently measure in situ void ratios. This paper describes the techniques used in the ground-freezing and various sampling programs and presents a summary of the results. Comparisons of void ratios measured for various types of samples and using geophysical logging are also made.Key words: CANLEX, ground freezing, sampling, geophysical logging, void ratio.

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 categoriesInsufficient payload (model declined to judge)
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 score0.876
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.216
Teacher spread0.205 · 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.

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

Citations22
Published2000
Admission routes3
Has abstractyes

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