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Record W7048011313

Inverse modelling of desorption tests to establish the hydraulic conductivity of unsaturated sands

2014· other· fr· W7048011313 on OpenAlexfundno aff

Bibliographic record

VenueCorpus Université Laval (Université Laval) · 2014
Typeother
Languagefr
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaHydro-QuébecUniversité Laval
KeywordsInverseHydraulic conductivityInverse methodConductivity
DOInot available

Abstract

fetched live from OpenAlex

Conductivité hydraulique non saturée est un paramètre important pour caractériser le comportement des sols non saturés. Ce paramètre peut être utilisé pour modéliser l'écoulement de l'eau dans les sols. Le défaut de mesure ou d'estimation de ce paramètre avec une précision fiable peut causer des incidents catastrophiques. La mesure de la conductivité hydraulique des sols non saturés peut être longue et coûteuse. Des méthodes directes et indirectes peuvent être utilisées pour établir ce paramètre. Dans cette étude, en vue de réduire le temps et le coût de la mesure de la conductivité hydraulique des sols non saturés nécessaires par les méthodes directes, la modélisation inverse a été utilisée comme une méthode indirecte pour estimer ce paramètre. Des essais de laboratoire ont été effectués pour trouver la courbe de rétention d'eau des différents échantillons de sol étudié. Les résultats expérimentaux obtenus ont été utilisés pour effectuer la modélisation inverse, et la conductivité hydraulique non saturée de chaque échantillon a été estimé.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.178
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 source (direct Gemma or distilled Codex), 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

Citations0
Published2014
Admission routes1
Has abstractyes

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