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The Soil Base Bearing Capacity Relevance Research in the Highway Overhaul Decision-Making

2013· article· en· W2030592086 on OpenAlexaff
Jie Sun, Qiang Sun, Ming Hua Wang

Bibliographic record

VenueApplied Mechanics and Materials · 2013
Typearticle
Languageen
FieldEngineering
TopicCivil and Geotechnical Engineering Research
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsBearing capacityGeotechnical engineeringExcavationEngineeringCivil engineeringBearing (navigation)ModulusBase (topology)Environmental scienceMining engineeringComputer scienceMaterials scienceMathematics

Abstract

fetched live from OpenAlex

Based on theexamples works of the road site excavation pits channels and supplemented by road non-destructive testing methods, this paper mainly adopts the road performance of the structural layers , main site designated point FWD test, soil base DCP test and soil base structure bearing capacity correlation. The results show that the existing common road on FWD detection inverse soil base modulus has a good linear relationship with soil base DCP measured modulus, in addition, measured soil base modulus with moisture content of the soil base also have a good linear relationship, but the three correlation does not comply with the actual situation of the road. Thus, before the decision making of the highway overhaul conservation , old Road usage evaluation, the road of non-destructive testing, the excavation pits survey and structural layers indicators detection are very necessary and effective methods.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.000
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 head0.025
GPT teacher head0.262
Teacher spread0.237 · 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 designObservational
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

Citations0
Published2013
Admission routes1
Has abstractyes

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