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Record W2947951852 · doi:10.1139/cgj-2018-0786

Geomaterial classification criteria for design and construction of driven steel H-piles

2019· article· en· W2947951852 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Geotechnical Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicMaterials Engineering and Processing
Canadian institutionsnot available
FundersWyoming Department of TransportationU.S. Department of Transportation
KeywordsPileGeotechnical engineeringFlowchartSoil waterLimitingBoundary (topology)GeologyEngineeringSoil scienceMathematics

Abstract

fetched live from OpenAlex

Methodologies are proposed to develop criteria for classifying geomaterials into soils, intermediate geomaterials (IGMs), and hard rocks to achieve efficient driven pile designs. IGMs were categorized into IGM-soils and IGM-rocks to reduce the uncertainties in pile resistance estimations associated with properties ranging from soils to rocks. A boundary between soils and IGM-soils was established based upon the performance of two static analysis methods measured in terms of the coefficients of variation between measured and estimated shaft resistances. A boundary between IGM-rocks and hard rocks was established by limiting the geotechnical resistance in IGM-rocks to the compressive strength of a steel pile. Finally, a geomaterial classification flowchart and sample design charts are proposed to facilitate the classification of geomaterials specifically for the design and construction of driven steel H-piles. The proposed framework can be adapted for other driven pile types.

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 score0.842
Threshold uncertainty score0.360

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 head0.018
GPT teacher head0.223
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