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Record W2033834020 · doi:10.1081/pfc-120004476

ADSORPTION, DESORPTION, AND MOBILITY OF TWO INSECTICIDES IN MALAYSIAN AGRICULTURAL SOILS

2002· article· en· W2033834020 on OpenAlexfundno aff
B. S. Ismail, A. O. S. Enoma, U. B. Cheah, K. Y. Lum, Z. Malik

Bibliographic record

VenueJournal of Environmental Science and Health Part B · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsnot available
FundersUniversity of Windsor
KeywordsDesorptionSoil waterAdsorptionAgricultureEnvironmental scienceEnvironmental chemistryChemistrySoil scienceGeographyArchaeology

Abstract

fetched live from OpenAlex

Laboratory studies utilizing radioisotopic techniques were conducted to determine the adsorption, desorption, and mobility of endosulfan (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9-methano-2,4,3-benzodioxanthiepin3-oxide) and methamidophos (O,S-dimethyl phosphorothioate) in sandy loam and clay soils of the Cameron Highlands and the Muda rice-growing area, respectively. High Freundlich adsorption distribution coefficients [Kads(f)] for endosulfan (6.74 and 18.75) and low values for methamidophos (0.40 and 0.98) were obtained in the sandy loam and clay soils, respectively. The observed Koc values for endosulfan were 350.85 (sandy loam) and 1143.19 (clay) while Koc values of 20.92 (sandy loam) and 59.63 (clay) were obtained for methamidophos. Log Kow of 0.40 and 1.25 were calculated for endosulfan as well as -1.96 and -1.21 for methamidophos in the sandy loam and clay soils, respectively. Desorption was common to both pesticides but the desorption capacity of methamidophos from each soil type far exceeded that of endosulfan. Soil thin layer chromatography (TLC) and column studies showed that while methamidophos was very mobile in both soils, endosulfan displayed zero mobility in clay soil.

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 score0.008
Threshold uncertainty score0.016

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)0.0000.000

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 head0.030
GPT teacher head0.270
Teacher spread0.240 · 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

Citations31
Published2002
Admission routes1
Has abstractyes

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Same venueJournal of Environmental Science and Health Part BSame topicPesticide and Herbicide Environmental StudiesFrench-language works237,207