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Record W2560742563 · doi:10.1111/1556-4029.13316

“Bath Salts” the New York City Medical Examiner Experience: A 3‐Year Retrospective Review

2016· article· en· W2560742563 on OpenAlexaff
Stephen J. deRoux, Billy Dunn

Bibliographic record

VenueJournal of Forensic Sciences · 2016
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsSt. Stephen's University
Fundersnot available
KeywordsCathinoneMedical examinerForensic toxicologyKhatMedicineAmphetamineDesigner drugToxicologyPharmacologyPoison controlEmergency medicineInjury preventionChemistryDrugInternal medicineChromatographyBiology

Abstract

fetched live from OpenAlex

"Bath salts" are synthetic derivatives of cathinones, compounds found in the leaves of Catha edulis, which possesses amphetamine-like properties. At the New York City Office of Chief Medical Examiner, we conducted a 3-year retrospective analysis of deaths in which cathinones were detected. Two categories emerged; those in which cathinones were a contributory cause of death (15 cases) and those in which they were an incidental finding (15 cases). Of the former group, 13 were associated with additional intoxicants; two deaths were attributed solely to cathinone intoxication, both survived 10 h: a man whose postmortem blood methylone concentration was 0.71 mg/L and a woman whose postmortem blood ethylone concentration was 1.7 mg/L. In the latter category, there were several individuals who had higher concentrations of cathinones than the above two, the highest being a blood methylone of 4.8 mg/L. Based upon our data and the literature presented, lethal concentrations of cathinones cannot be established.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.119
GPT teacher head0.436
Teacher spread0.317 · 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 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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