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Record W2902629504 · doi:10.1111/add.14474

Illicit fentanyls in the opioid street market: desired or imposed?

2018· article· en· W2902629504 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAddiction · 2018
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsDalhousie University
FundersNational Institute on Drug Abuse
KeywordsFentanylHeroinMedical prescriptionOpioidBusinessEconomic shortageSearch costDeep WebMedicineAnesthesiaEconomicsPharmacologyDrugThe InternetMicroeconomicsComputer scienceGovernment (linguistics)

Abstract

fetched live from OpenAlex

BACKGROUND: Illicitly manufactured fentanyl and its analogues are appearing in countries throughout the world, often disguised as heroin or counterfeit prescription pills, with resulting high overdose mortality. Possible explanations for this phenomenon include reduced costs and risks to heroin suppliers, heroin shortages, user preferences for a strong, fast-acting opioid and the emergence of Dark Web cryptomarkets. This paper addresses these potential causes and asks three questions: (1) can users identify fentanyl; (2) do users desire fentanyl; and (3) if users want fentanyl, can they express this demand in a way that influences the supply? ARGUMENT/ANALYSIS: Existing evidence, while limited, suggests that some users can identify fentanyl, although not reliably, and some desire it, but because fentanyl is frequently marketed deceptively as other drugs, users lack information and choice to express demand effectively. Even when aware of fentanyl's presence, drug users may lack fentanyl-free alternatives. Cryptomarkets, while difficult to quantify, appear to offer buyers greater information and competition than offline markets. However, access barriers and patterns of fentanyl-related health consequences make cryptomarkets unlikely sources of user influence on the fentanyl supply. Market condition data indicate heroin supply shocks and shortages prior to the introduction of fentanyl in the United States and parts of Europe, but the much lower production cost of fentanyl compared with heroin may be a more significant factor CONCLUSION: Current evidence points to a supply-led addition of fentanyl to the drug market in response to heroin supply shocks and shortages, changing prescription opioid availability and/or reduced costs and risks to suppliers. Current drug users in affected regions of the United States, Canada and Europe appear largely to lack both concrete knowledge of fentanyl's presence in the drugs they buy and access to fentanyl-free alternatives.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.020
GPT teacher head0.282
Teacher spread0.261 · 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