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Clay effects on the contact angle and water drop penetration time of model soils

2010· article· en· W2084778406 on OpenAlexfundno aff
D. A. L. Leelamanie, Jutaro Karube, Aya Yoshida

Bibliographic record

VenueSoil Science & Plant Nutrition · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersMcGill University
KeywordsKaoliniteSoil waterContact angleOrganic matterClay mineralsWater contentRelative humiditySessile drop techniqueDrop (telecommunication)Water repellentSoil scienceChemistryMineralogyMaterials scienceEnvironmental scienceGeologyGeotechnical engineeringComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Clay is an important factor that affects soil water repellency. The purpose of the present study was to assess the effects of clay content on contact angle and water drop penetration time (WDPT), and to examine their relationship. Model soils were prepared with silica sand and kaolinite, and hydrophobized using stearic acid (SA). The effect of kaolinite on the contact angle changed with the hydrophobic organic matter content of the model soils. The contact angles of organic matter free samples increased with increasing kaolinite content. This was explained by a decrease in the surface-free energy of kaolinite with the adsorption of water at 57% relative humidity. In samples with SA content above 1.6 g kg−1, the contact angle decreased with increasing kaolinite content because the hydrophobizing effect of SA was lower at higher kaolinite content owing to the lower extent of hydrophobic organic coatings. Kaolinite increased the WDPT in non-repellent soils, but decreased the WDPT in slightly to severely repellent soils. Clay effects on the contact angle and WDPT were not comparable and, consequently, the relationship between contact angle and WDPT was found to be non-uniform at different clay contents.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.006
GPT teacher head0.193
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 teacher head, 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

Citations17
Published2010
Admission routes1
Has abstractyes

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