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Record W2314528083 · doi:10.1111/1556-4029.12999

Manners of Death in Drug‐Related Fatalities in Florida

2016· article· en· W2314528083 on OpenAlexaff
Dayong Lee, Chris Delcher, Mildred M. Maldonado‐Molina, Jon R. Thogmartin, Bruce A. Goldberger

Bibliographic record

VenueJournal of Forensic Sciences · 2016
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsGolder Associates (Canada)Office of the Chief Medical Examiner
FundersCenters for Disease Control and PreventionMinisterio de Economía y Competitividad
KeywordsHomicideAccidentalMedicineDrug overdoseForensic toxicologyPoison controlInjury preventionDrugCause of deathSuicide preventionMedical emergencyPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

To understand the mortality patterns among drug users and potential risk factors, we evaluated drug-related deaths reported to the Florida Medical Examiners Commission from 2001 to 2013, by substances, demographics, and manner of death. The annual drug-related fatalities increased by 57% from 2001 to 2013 (total n = 100,882); 51.8% were accidental, 7.9% homicide, 18.6% natural, and 19.6% suicide. The different manners of death exhibited distinct demographic profiles and drug composition. The gender gap was more prominent in homicide. Age ≥55 years was more closely associated with natural death and suicide. Age <35 years and central nervous system (CNS) stimulants including amphetamines and cocaine showed higher relative risks for accidental death and homicide, whereas CNS depressants including benzodiazepines, carisoprodol, opioids, and zolpidem were more strongly associated with accidental death and/or suicide. The findings aid in identifying populations more vulnerable to drug-related deaths, developing targeted interventions and thereby improving efficiency of preventive efforts.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.162

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.292
Teacher spread0.271 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2016
Admission routes1
Has abstractyes

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