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Record W2105804759 · doi:10.1071/sr14258

Weighting the differential water capacity to account for declining hydraulic conductivity in a drying coarse-textured soil

2015· article· en· W2105804759 on OpenAlexaff
C. D. Grant, P. H. Groenevelt

Bibliographic record

VenueSoil Research · 2015
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of Guelph
FundersUniversidade de São PauloUniversity of Adelaide
KeywordsHydraulic conductivitySoil waterWater potentialPedotransfer functionContext (archaeology)Water retention curveSoil scienceMathematicsThermal diffusivityWater retentionWater contentEnvironmental scienceGeotechnical engineeringGeologyThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Water availability to plants growing in coarse-textured soils during a drying cycle relies on the declining abilities of the soil to release water (differential water capacity) and to deliver it to the plant (unsaturated hydraulic conductivity) under varying evaporative demand. In this context, the availability of water can be quantified using the concept of the integral water capacity, IWC, in which the differential water capacity is weighted by means of a restrictive hydraulic function before integrating. We argue here that the diffusivity is an appropriate component of the restrictive hydraulic function, which leads to the employment of the so-called ‘matric flux potential’ (which we propose to re-name as the ‘matric flux transform’). As the starting point to apply the diffusivity function, we choose the inflection point of the water-retention curve drawn on semi-log paper, which, for the Groenevelt–Grant equation, occurs at a matric head, h, of precisely k0 metres. An illustrative example of the procedures is provided for a coarse-textured soil, which reveals that the restrictive function may not be sufficiently restrictive for all cases. We therefore apply an additional weighting coefficient to account for varying sensitivity of different plants to hydraulic restrictions.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.001
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 head0.158
GPT teacher head0.344
Teacher spread0.187 · 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 designBench or experimental
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

Citations16
Published2015
Admission routes1
Has abstractyes

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