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Record W2151465389

The health and economic effects of counterfeit drugs.

2014· article· en· W2151465389 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Quality and Counterfeiting
Canadian institutionsnot available
Fundersnot available
KeywordsCounterfeitCounterfeit DrugsBusinessMedicineData scienceComputer sciencePolitical science
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Counterfeit drugs comprise an increasing percentage of the US drug market and even a larger percentage in less developed countries. Counterfeit drugs involve both lifesaving and lifestyle drugs. OBJECTIVE: To review the health and economic consequences of counterfeit drugs on the US public and on the healthcare system as a whole. METHOD: This comprehensive review of the literature encompassed a search of MEDLINE/PubMed, Google Scholar, and ProQuest using the keywords "counterfeit drugs," "counterfeit medicines," "fake drugs," and "fake medicines." A search of the various FiercePharma daily newsletter series on the healthcare market was also conducted. In addition, the US Food and Drug Administration and the World Health Organization websites were reviewed for additional information. DISCUSSION: The issue of counterfeit drugs has been growing in importance in the United States, with the supply of these counterfeit drugs coming from all over the world. Innovation is important to economic growth and US competitiveness in the global marketplace, and intellectual property protections provide the ability for society to prosper from innovation. Especially important in terms of innovation in healthcare are the pharmaceutical and biopharmaceutical industries. In addition to taking income from consumers and drug companies, counterfeit drugs also pose health hazards to patients, including death. The case of bevacizumab (Avastin) is presented as one recent example. Internet pharmacies, which are often the source of counterfeit drugs, often falsely portray themselves as Canadian, to enhance their consumer acceptance. Adding to the problems are drug shortages, which facilitate access for counterfeits. A long and convoluted supply chain also facilitates counterfeits. In addition, the wholesale market involving numerous firms is a convenient target for counterfeit drugs. Trafficking in counterfeits can be extremely profitable; detection of counterfeits is difficult, and the penalties are modest. CONCLUSION: Counterfeit drugs pose a public health hazard, waste consumer income, and reduce the incentive to engage in research and development and innovation. Stronger state licensure supervision of drug suppliers would be helpful. Technological approaches, such as the Radio Frequency Identification devices, should also be considered. Finally, counterfeit drugs may raise concerns among consumers about safety and reduce patient medication adherence.

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 score0.984
Threshold uncertainty score0.147

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 head0.024
GPT teacher head0.299
Teacher spread0.276 · 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