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Record W1541607012

Sprucing Up Patent Law

2011· article· en· W1541607012 on OpenAlexaff
David Vaver

Bibliographic record

VenueeYLS (Yale Law School) · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsYork University
Fundersnot available
KeywordsIntellectual propertyPatent lawArgument (complex analysis)Law and economicsLawInventionPatent infringementBusinessInterpretation (philosophy)Patent trollPolitical scienceEconomicsComputer scienceMedicine
DOInot available

Abstract

fetched live from OpenAlex

This paper, commissioned for the now defunct UK Strategic Advisory Board for Intellectual Property, looks at some aspects of UK patent law and asks whether some of the activities it rewards deserve the protection they get. The argument is that patent law should more precisely match and reward the advance the inventor discloses, that patents should not be granted for activities that need no stimulus or are already adequately stimulated by other intellectual property laws, that specifications should disclose all the inventor knows about the invention to as wide an audience as possible, that only activities the patent holder and the public fairly expect to be included with the patent’s claims should be caught, and that patents should be enforced in ways that do not unfairly benefit patentees and unnecessarily restrain industry. While the paper deals with the specifics of U.K. law, many of the general points it makes - for example, on overbroad patents, overlapping protection, disclosure of best methods of practising the invention, overbroad claim interpretation and the injunction remedy - apply equally to the laws of other countries.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score0.993

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)0.0080.014

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 head0.135
GPT teacher head0.224
Teacher spread0.089 · 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 designTheoretical or conceptual
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

Citations1
Published2011
Admission routes1
Has abstractyes

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