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Record W2536887084 · doi:10.1002/hup.2548

Captagon: use and trade in the Middle East

2016· review· en· W2536887084 on OpenAlexfundno aff
Ahmed Al-Imam, Rita Santacroce, Andrés Román-Urrestarazu, Robert P. Chilcott, Giuseppe Bersani, Giovanni Martinotti, Ornella Corazza

Bibliographic record

VenueHuman Psychopharmacology Clinical and Experimental · 2016
Typereview
Languageen
FieldMedicine
TopicPharmaceutical Quality and Counterfeiting
Canadian institutionsnot available
FundersPublic Health AgencyPublic Health Agency of CanadaWorld Health Organization
KeywordsMiddle EastGeographyArchaeology

Abstract

fetched live from OpenAlex

BACKGROUND: Fenetheylline, a psychostimulant drug, often branded as Captagon, is a combination of amphetamine and theophylline. Since the cessation of its legal production in 1986, counterfeited products have been produced illicitly in south-east Europe and far-east Asia. Its profitable trade has been linked to terrorist organizations, including Islamic State of Iraq and the Levant. This study aims to reach up-to-date data, concerning the Captagon e-commerce and use in the Middle East. METHODS: A multi-staged and multi-lingual literature search was carried out. A list of prespecified keywords was applied across medical and paramedical databases, web and Dark web, search engines, social communication media, electronic commerce websites, media networks, and the Global Public Health Intelligence Network database. RESULTS: The use of Captagon as a stimulant in terrorist settings has been marginally covered in the literature. Data can widely be retrieved from Google and AOL search engines, YouTube, and Amazon e-commerce websites, and to a lesser extent from Alibaba and eBay. On the contrary, Middle Eastern e-commerce websites yielded almost no results. Interestingly, the Dark web generated original data for Captagon e-commerce in the Middle East. CONCLUSION: Further investigations are needed on the role that psychoactive drugs play in terrorist attacks and civil war zones. Unless a comprehensive methodological strategy, inclusive of unconventional methods of research, is implemented, it will not be feasible to face such a threat to humanity.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.009
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.520
GPT teacher head0.558
Teacher spread0.039 · 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 designNot applicable
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

Citations65
Published2016
Admission routes1
Has abstractyes

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