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A meta‐analysis of marijuana, cocaine and opiate toxicology study findings among homicide victims

2009· review· en· W2141714341 on OpenAlexaboutno aff
Joseph B. Kuhns, David B. Wilson, Edward R. Maguire, Steph Ainsworth, Tammatha A. Clodfelter

Bibliographic record

VenueAddiction · 2009
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsnot available
FundersGeorge Mason University
KeywordsHomicideMedicineForensic toxicologyOpiatePoison controlInjury preventionOccupational safety and healthHuman factors and ergonomicsTest (biology)Suicide preventionPsychiatryPsychologyEnvironmental healthBiologyInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT Aim To synthesize the results of marijuana, cocaine and opiate drug toxicology studies of homicide victims and examine variation in results across person and setting characteristics. Methods A meta-analysis of 18 independent studies identified from an extensive review of 239 published articles that met the inclusion criteria of reporting marijuana, cocaine and/or opiate toxicology test results for homicide victims. A total of 28 868 toxicology test results derived from 30 482 homicide victims across five countries were examined. Results On average, 6% of homicide victims tested positive for marijuana, 11% tested positive for cocaine, and 5% tested positive for opiates. The proportion of homicide victims testing positive for illicit drugs has increased over time. Age had a strong curvilinear relationship with toxicology test results, but gender differences were not apparent. Hispanic and African American homicide victims were more likely to test positive for cocaine; Caucasians were most likely to test positive for opiates. Cocaine use appeared to be related to increased risk of death from a firearm and was a greater risk factor for violent victimization in the United States than in Newfoundland and Scandinavia. Conclusion There are relatively few studies of illicit drug toxicology reports from homicide victims that allow for cross-cultural comparisons. This study provides a basis for comparing future local toxicology test results to estimates from existing research.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.154
GPT teacher head0.445
Teacher spread0.291 · 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 teacher head, not a consensus.

Study designMeta-analysis
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

Citations47
Published2009
Admission routes1
Has abstractyes

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