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Record W1765239159 · doi:10.1139/cgj-2012-0121

Influence of infiltration on the periodic re-activation of slow movements in an overconsolidated clay slope

2012· article· en· W1765239159 on OpenAlexvenueno aff
Paolo Tommasi, Daniela Boldini, Giada Caldarini, Niccolò Coli

Bibliographic record

VenueCanadian Geotechnical Journal · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
FundersU.S. Department of Agriculture
KeywordsPiezometerPore water pressureGeologyGeotechnical engineeringLandslideInclinometerHydraulic conductivitySlope stabilityGroundwaterAquiferSoil scienceSoil water

Abstract

fetched live from OpenAlex

In Orvieto (central Italy), overconsolidated clay slopes are affected by intermittent slow movements at the top of the clay formation and within the landslide debris cover. Monthly data from inclinometers, Casagrande piezometers, and rainfall gauges show that velocity, pore pressure, and rainfall are closely related. A relationship is suggested to predict slope re-activation using rainfall history alone, once a pore pressure threshold has been reached and response of pore pressures to rainfall is understood. Pore pressures have been continuously monitored through vibrating wire cells. The threshold for shallow movements, critical for infrastructures and buildings, was identified by comparing displacement histories of a shallow movement, representative of many other ones recognized over the slope, and pore pressure, both measured at the centre of the sliding mass. The impact of infiltrated rainfall on groundwater flow was investigated through transient seepage analyses. Seepage analyses performed using hydraulic properties from laboratory and in situ tests do not fully depict the observed pore pressures because field data miss some structural characters and lithologic variations. The hydraulic properties of the shallower model layers were refined, based on field observations and interpretation of monitoring data, to have a good match between computed and measured pore pressures. Once the model is tested at different locations along a slope, it could be used to predict movement re-activation using only rainfall data.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.230
Teacher spread0.217 · 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

Citations34
Published2012
Admission routes1
Has abstractyes

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