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Record W1597558136

Should All Drugs Be Patentable?: A Comparative Perspective

2014· article· en· W1597558136 on OpenAlexaboutno aff
Cynthia M. Ho

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectual propertyTRIPS architectureScope (computer science)Patentable subject matterHarmPerspective (graphical)TRIPS AgreementLaw and economicsBusinessPublic economicsPipeline (software)Political scienceEconomicsPatent lawEngineeringLawComputer sciencePatentability
DOInot available

Abstract

fetched live from OpenAlex

Although there has been substantial discussion of the proper scope of patentable subject matter in recent years, drugs have been overlooked. This Article begins to address that gap with a comparative perspective. In particular, this Article considers what is permissible under the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS), as well as how India and Canada have utilized TRIPS flexibilities in different ways to properly reward developers of valuable new drugs, while also considering the social harm of higher prices beyond an initial patent term on drugs.\n This Article brings valuable insight into this area at a critical time. Many have noted that the industry is in a crisis because, despite exponentially increasing expenditures, the number of new drugs produced has been stagnant. Moreover, a predominant number of the slim pipeline features drugs that are not highly innovative. At the same time, the industry and some academics are seeking to increase protection of drugs in the United States and beyond, which could further exacerbate existing problems.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.297
GPT teacher head0.291
Teacher spread0.007 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations5
Published2014
Admission routes1
Has abstractyes

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