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Record W4285384827 · doi:10.2105/ajph.2022.306881

Xylazine and Overdoses: Trends, Concerns, and Recommendations

2022· article· en· W4285384827 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Public Health · 2022
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsKimberly-Clark (Canada)
Fundersnot available
KeywordsXylazineMedicinePublic healthHarmEnvironmental healthHarm reductionDrugSedativeDrug overdosePharmacologyIntensive care medicineAnesthesiaPoison controlKetaminePolitical scienceNursingLaw

Abstract

fetched live from OpenAlex

Xylazine is a nonopioid veterinary anesthetic and sedative that is increasingly detected in the illicit drug supply in the United States. Data indicate a striking prevalence of xylazine among opioid-involved overdose deaths. The emergence of xylazine in the illicit drug supply poses many unknowns and potential risks for people who use drugs. The public health system needs to respond by increasing testing to determine the prevalence of xylazine, identifying its potential toxicity at various exposure levels, and taking mitigating action to prevent harms. Currently, there is little testing capable of identifying xylazine in drug supplies, which limits the possibility of public health intervention, implementation of harm reduction strategies, or development of novel treatment strategies. (Am J Public Health. 2022;112(8):1212–1216. https://doi.org/10.2105/AJPH.2022.306881 )

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.873
Threshold uncertainty score0.475

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 head0.071
GPT teacher head0.372
Teacher spread0.301 · 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