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Record W2029179379 · doi:10.1002/ajim.20147

Suicide and exposure to organophosphate insecticides: Cause or effect?

2005· review· en· W2029179379 on OpenAlexaff
Leslie London, Alan J. Flisher, Catharina Wesseling, Donna Mergler, Hans Kromhout

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2005
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Exposure and Toxicity
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsMedicineOrganophosphatePoison controlPesticideDepression (economics)Injury preventionAnimal studiesSuicide preventionEnvironmental healthOccupational safety and healthEpidemiologyToxicologyPsychiatryInternal medicineBiologyPathologyEcology

Abstract

fetched live from OpenAlex

BACKGROUND: Suicide using pesticides as agent is recognized as a major cause of pesticide poisoning. METHODS: A literature review of mortality and morbidity studies related to suicide among pesticide-exposed populations, and of human and animal studies of central nervous system toxicity related to organophosphate (OP) pesticides was performed. RESULTS: Suicide rates are high in farming populations. Animal studies link OP exposure to serotonin disturbances in the central nervous system, which are implicated in depression and suicide in humans. Epidemiological studies conclude that acute and chronic OP exposure is associated with affective disorders. Case series and ecological studies also support a causal association between OP use and suicide. CONCLUSIONS: OPs are not only agents for suicide. They may be part of the causal pathway. Emphasizing OPs solely as agents for suicide shifts responsibility for prevention to the individual, reducing corporate responsibility and limiting policy options available for control.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.088
GPT teacher head0.334
Teacher spread0.246 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations186
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Industrial MedicineSame topicPesticide Exposure and ToxicityFrench-language works237,207