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Record W2052701745 · doi:10.5539/ibr.v6n1p211

Pharmacokinetic Tests: A Public Policy Tool of Science, Technology, and Innovation in Pharmaceutical Drugs for Brazil

2012· article· en· W2052701745 on OpenAlexvenueno aff
Marcelino José Jorge, Georg Weinberg, Marina Filgueiras Jorge

Bibliographic record

VenueInternational Business Research · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsBioequivalenceIncentivePharmaceutical industryBioavailabilityGovernment (linguistics)BusinessPublic economicsPublic policyScope (computer science)PharmacologyAccountingEconomicsMedicineEconomic growthComputer science

Abstract

fetched live from OpenAlex

Bioavailability (BA) tests measure the variation over time in the availability, in the bloodstream, of the compound contained in a medicine. Bioequivalence (BE) tests compare the bioavailability of drugs with the same therapeutic indication, administered by the same route and at the same dose. Given the objectives of social regulation in the 1990s, the advantages of these tests explained their emergence in Brazil. The current article thus aimed to review the historical background for the regulatory framework of the Brazilian pharmaceutical industry and the organizational characteristics of BA/BE testing, and to highlight the latter’s importance for the country’s pharmaceutical policy within an open-economy growth model. The conclusion is that the number of certified centers in Brazil as of 2008 signaled the risk of an increase in the degree of concentration of BA/BE testing, while the perspective of cooperative research in the Brazilian government centers represented an incentive for innovation.

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)0.016
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.048
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0020.005
Scholarly communication0.0070.007
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.167
GPT teacher head0.461
Teacher spread0.295 · 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.

Study designQualitative
Domainnot available
GenreEmpirical

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
Published2012
Admission routes1
Has abstractyes

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