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Record W7135897562

The medicaments containing pseudoephedrine - material for illegal production of metamphetamine

2009· dissertation· cs· W7135897562 on OpenAlexaboutno aff
Stanislav Havlíček

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2009
Typedissertation
Languagecs
FieldMedicine
TopicPharmacology and Obesity Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsPseudoephedrineEphedrinePharmacyProduction (economics)Consumption (sociology)Drugs of abuse
DOInot available

Abstract

fetched live from OpenAlex

1 SUMMARY MEDICINE CONTAINING PSEUDOEPHEDRINE - RAW MATERIALS FOR CLANDESTINE PRODUCTION OF METHAMPHETAMINE Author: Havlíček S., Métis, Pharmacy in Stod, Czech Republic Tutor: Kotlářová J., Dept. of Social and Clinical Pharmacy, Faculty of Pharmacy in Hradec Kralove, Charles University in Prague,Czech Republic In the Czech Republic, the clandestine methamphetamine (pervitin) production appeared in 1970s. Ephedrin used to be a main source for methamphetamine production till the factory for ephedrine output in Roztoky (in 2004) was closed down. Since this moment a pseudoephedrine gained from ordinarily available medicaments has become very popular base material for this illegal production. An expansion of the illicit "home-based" methamphetamine manufactories is supported by very easy accessibility and also by poor regulation of these medicaments containing pseudoephedrine Another reason is the low price of the legally obtainable medication: around 200 CZK per 1g of pseudoephedrine. Pharmacies have suddenly become suppliers of drug gangs. However, they cannot prevent such situation under current legislation. Tightening regulations may help to solve the problem, but it seems unlikely to happen taken into account the large profits at stake. Sales volume of pharmaceuticals containing pseudoephedrine (Modafen,...

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)0.000
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0310.011

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 head0.010
GPT teacher head0.287
Teacher spread0.277 · 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
GenreOther

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

Citations0
Published2009
Admission routes1
Has abstractyes

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Same venueDigital Repository (National Repository of Grey Literature)Same topicPharmacology and Obesity TreatmentFrench-language works237,207