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Record W2171333394 · doi:10.1080/09593330.2011.567300

Sorption of endosulphan sulphate in soil organic matter

2011· article· en· W2171333394 on OpenAlexaff
Raja Chowdhury, James W. Atwater, Ken J. Hall, P. Parkinson

Bibliographic record

VenueEnvironmental Technology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSorptionSolubilityIonic strengthChemistryEnvironmental chemistryCalciumOrganic matterInorganic chemistryNuclear chemistryAqueous solutionOrganic chemistryAdsorption

Abstract

fetched live from OpenAlex

Sorption of endosulphan sulphate in soil organic matter was investigated using Standard Elliot soil humic acid (HA) and soil fulvic acid (FA) at two ionic strengths (0.001 and 0.01). It was observed that divalent calcium ion and ionic strength affect the sorption of endosulphan sulphate in HA. All the experiments were carried out at pH 6.7 +/- 0.1. In the presence and absence of calcium (ionic strength 0.001), the solubility enhancement method was used to estimate the sorption coefficients of endosulphan sulphate in HA. For FA, the solubility enhancement method was used to estimate the sorption coefficients at an ionic strength of 0.001 (in the presence of calcium) and 0.01. The presence of calcium was found to significantly enhance (alpha = 0.01) the solubility of endosulphan sulphate in HA. Sorption coefficients at pH 6.7, obtained using the solubility enhancement method, were found to be 10-21 L/g in HA and 6 L/g in FA (in the presence of calcium). Increase in ionic strength from 0.001 to 0.01 decreased the sorption of endosulphan sulphate in HA. The effect of ionic strength and calcium on the sorption of endosulphan sulphate was most satisfactorily explained on the basis of the Donnan volume.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0460.006

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 head0.180
Teacher spread0.174 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2011
Admission routes1
Has abstractyes

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