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Record W1596235566 · doi:10.5772/16749

Geochemical Indicators of Organo-Chloro Pesticides in Lake Sediments

2011· book-chapter· en· W1596235566 on OpenAlexaboutno aff
Stephen Kudom

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
Fundersnot available
KeywordsPesticideGeologyGeochemistryEnvironmental chemistryEnvironmental scienceHydrology (agriculture)Geotechnical engineeringChemistryEcologyBiology

Abstract

fetched live from OpenAlex

The study area, Lake Liangzi is regarded as one of the least polluted lakes in Central China. This is because the local people have made great efforts to protect the lake from the use of all forms of chemicals for crop and fish farming activities. Besides this measure, other uses such as recreation, water supply and electricity production are also not permitted. In fact, it is noteworthy to mention that the lake supplies one of the most popular and delicious types of fish in Central China. It is called "Wuchang fish" and is very popular in most leading restaurants in Central China and quite expensive for its delicacy. However, since modern technology has revealed that organic compounds such as Organo chloro-pesticides (OCPs) could be deposited into lakes and other water bodies from remote areas, far from the point of application, it will be worthwhile to undertake investigation to ascertain whether the lake is free from these contaminants. The path of investigation used dated sediment core since according to It should be mentioned that this volume of work is part of the author's PhD research and also one of the pioneering research works on pesticides in the lake. OCPs are a group of common pollutants belonging to the class of pollutants called Persistent Organic Pollutants (POPs). One of the most important families of Persistent Organic Pollutants (POPs) that has a significant impact upon the environment are pesticides. According to Sierra Club of Canada, (1998), pesticides are the only man-made toxic chemicals deliberately released over large areas. They are poisonous almost by definition. Pesticides poison the food chain, contaminate water supplies and are implicated in the declining populations of many biotic species. In this study, a single drilled undisturbed sedimentary core extracted from Lake Liangzi in Central China was analyzed for target compounds using highly sophisticated instruments. Even though other organic compounds (such as Polycyclic Hydrocarbons; PAHs, Aliphatic Hydrocarbons; Ahs and heavy metals) were detected, they are not discussed in this article.. The focus of discussion are the organocgloro-pesticides, including DDT, DDD and DDE and the geochemical relationship between them.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.866
Threshold uncertainty score1.000

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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.001

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 head0.013
GPT teacher head0.224
Teacher spread0.211 · 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 designBench or experimental
Domainnot available
GenreOther

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

Citations0
Published2011
Admission routes1
Has abstractyes

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