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Record W2161375308 · doi:10.4141/s99-071

Kinetics and equilibria of Metribuzin sorption on model soil components

2000· article· en· W2161375308 on OpenAlexaffvenue
Rufus Sha’Ato, Erwin Buncel, D. G. Gamble, Gary W. vanLoon

Bibliographic record

VenueCanadian Journal of Soil Science · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsQueen's UniversityUniversity of Calgary
Fundersnot available
KeywordsSorptionKaoliniteChemistryMetribuzinHumic acidClay mineralsMontmorilloniteEnvironmental chemistrySoil waterAdsorptionInorganic chemistryMineralogySoil scienceGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

Sorption to solid phase materials is known to significantly affect the transport, bioavailability and ultimate fate of organic contaminants in soils and sediments. In order to develop a complete description of the fate of these compounds, it is necessary to understand both equilibrium interactions and rates and mechanisms of the sorption processes. The object of the present study was to investigate both these factors with respect to the sorption of metribuzin on model soil components, including the clay minerals kaolinite and montmorillonite, amorphous iron and aluminum hydrous oxides and humic acid. In all cases, uptake followed a similar course; there was a very rapid initial sorption process followed by continued uptake at a much slower rate. Rate constants for the slow sorption were smallest for the clay minerals, intermediate for the hydrous oxides and greatest for humic acid. Labile sorption capacities for metribuzin on the humic acid and clay minerals were also determined; the organic material had the largest capacity, and montmorillonite had a greater capacity than kaolinite. Key words: Metribuzin, sorption, clay minerals, humic material

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.020
GPT teacher head0.217
Teacher spread0.197 · 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

Citations20
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Soil ScienceSame topicPesticide and Herbicide Environmental StudiesFrench-language works237,207