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Record W2137142271 · doi:10.1139/cgj-2015-0027

Cone penetration test (CPT)-based stratigraphic profiling using the wavelet transform modulus maxima method

2015· article· en· W2137142271 on OpenAlexvenueno aff
Jianye Ching, Jiun-Shiang Wang, C. Hsein Juang, Chih-Sheng Ku

Bibliographic record

VenueCanadian Geotechnical Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsCone penetration testWavelet transformMathematicsMaxima and minimaWaveletComputationMaximaMathematical analysisGeometryGeologyAlgorithmGeotechnical engineeringComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, a stratigraphic profiling approach is proposed based on the soil behavior type index, Ic, obtained from the cone penetration test (CPT). The basic idea of this approach is simple: the layer boundaries can be identified as the points at which a change occurs in the Ic profile. It is shown that these change points can be easily identified using the wavelet transform modulus maxima (WTMM) method. This method is able to accurately pinpoint the locations of change points in the Ic profile and to produce graphs and plots that fit well with engineers’ methods of visualization and intuition. Moreover, by virtue of the fast Fourier transform, the computation is very fast. Case studies show that the WTMM method is effective for the detection of change points in the Ic profile. It is also capable of detecting thin soil layers.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.237
Teacher spread0.208 · 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 designBench or experimental
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

Citations77
Published2015
Admission routes1
Has abstractyes

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