MétaCan
Menu
Back to cohort
Record W3088349461 · doi:10.2196/17684

The Impact of Brexit on the Pharmaceutical Supply Chain of the United Kingdom: Scoping Review Protocol

2020· article· en· W3088349461 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.

venuePublished in a venue whose home country is Canada.
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

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Systems and Challenges
Canadian institutionsnot available
FundersEIT HealthUniversity of Oxford
KeywordsBrexitProtocol (science)Supply chainBusinessComputer scienceMedicineInternational tradeMarketingEuropean unionAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The continuing uncertainty around Brexit has caused concern in the pharmaceutical industry and among health care professionals and patients. The exact consequences of Brexit on the pharmaceutical supply chain in the United Kingdom will depend on whether a deal is reached and what it entails, but it is likely to be affected by the withdrawal of the United Kingdom from the European Union. Regulatory issues and delays in supply have the potential to negatively affect the ability of UK residents to receive an adequate and timely supply of necessary medicines. OBJECTIVE: The purpose of this protocol is to provide an overview and critical analysis of current perspectives on the effect of Brexit on the UK pharmaceutical supply chain. METHODS: The PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guidelines will be used to structure this protocol. A systematic search of MEDLINE, EMBASE, PsycINFO, Healthcare Management Information Consortium (HMIC), Cochrane, Web of Science, Business Source Complete, EconLit, and Economist Intelligence Unit will be conducted, as well as a Google and Nexis.UK search for grey literature such as reports, opinion pieces, and press releases. Two reviewers will independently screen the titles and abstracts of identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. One reviewer will extract data from the included studies into a standardized form, which will be validated by a second reviewer. Risk of bias will be assessed using the Cochrane Collaboration Risk of Bias tool for any randomized controlled trials; quality will be assessed using the relevant Critical Appraisal Skills Programme (CASP) checklists; and grey literature will be assessed using the Authority, Accuracy, Coverage, Objectivity, Date, Significance (AACODS) checklist. Outcomes include the agreement between sources on the potential, likelihood, and severity of the consequences of Brexit on the UK pharmaceutical supply chain. RESULTS: Results will be included in the scoping review, which will be published in 2020. CONCLUSIONS: This scoping review will summarize the currently expected consequences of Brexit on the UK pharmaceutical supply chain. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/17684.

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)0.010
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
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 head0.800
GPT teacher head0.744
Teacher spread0.056 · 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