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Record W2004082492 · doi:10.1139/s03-004

Mesh size selection in a soil-biosphere-atmosphere transfer model

2003· article· en· W2004082492 on OpenAlexvenueno aff
A. Mangeney, D. Aubert, Jérôme Demarty, Catherine Ottlé, Isabelle Braud

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsDiscretizationBiosphereHeat transferMass transferAtmosphere (unit)Environmental scienceSoil waterHorizonSoil scienceMechanicsGeologyMeteorologyMathematicsPhysicsGeometry

Abstract

fetched live from OpenAlex

The aim of this paper is to show the impacts of the vertical discretization in a physical soil numerical model on the calculation of the heat and mass transfer equations. The Simple Soil Plant Atmosphere Transfer (SISPAT) model was used in this study. It solves the coupled equations of mass and energy transfers in the soil and can deal with several horizons for vertically non-homogeneous soils. A series of numerical experiments have been performed to assess the influence of the vertical resolution grid on the simulation of the heat and water transfers using the SISPAT model in a one horizon configuration (homogeneous soil). In the studied case, a minimum of 20 layers has been found for a single 1.4 m thick horizon. Based on this analysis, numerical tests have been performed using SISPAT in a four horizons configuration. Key words: soil–atmosphere exchanges, numerical model, vertical resolution, heat and mass transfer.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.003
GPT teacher head0.155
Teacher spread0.152 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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