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Record W2081022373 · doi:10.1139/t02-037

Mechanical behavior of silty soils of the Venice lagoon as a function of their grading characteristics

2002· article· en· W2081022373 on OpenAlexvenueno aff
Simonetta Cola, Paolo Simonini

Bibliographic record

VenueCanadian Geotechnical Journal · 2002
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsSiltGeologyGeotechnical engineeringSoil waterGrain sizeAtterberg limitsGrading (engineering)Particle-size distributionSedimentary depositional environmentStructural basinSoil scienceGeomorphologyParticle sizeCivil engineeringEngineering

Abstract

fetched live from OpenAlex

The main feature of the shallowest quaternary basin of the well-renowned historic city of Venice, Italy and its surrounding lagoon, is the presence, apparently without any regular trend in depth and site, of a predominant silt fraction. This is always combined with clay and (or) sand, forming a chaotic and erratic interbedding of different sediments whose mineralogy is however variable in a relatively narrow range due to a unique geological origin and a common depositional environment. After a brief description of the basic soil indexes of the Venice lagoon soil, the present study, based on a comprehensive geotechnical laboratory investigation, describes the range of variation of the most relevant time-independent geotechnical properties. Moreover, a new grain size index, combining the geometrical characteristics of the particle distribution, is introduced. It is shown that the soil response at large and very small strains can be related to this grain size index, which appears to be able to include the influence of the soil grading on the description of the overall mechanical behavior.Key words: silt, mechanical behavior, Venice soil, grain-size index, laboratory investigation, critical state parameters.

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 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 score0.640
Threshold uncertainty score0.618

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 integrity0.0000.001
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 head0.013
GPT teacher head0.180
Teacher spread0.167 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations57
Published2002
Admission routes1
Has abstractyes

Explore more

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