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Record W6991950013

Intellectual Property Management: Assessing Stakeholder Knowledge Regarding Obtaining Valid Patent Rights

2013· article· en· W6991950013 on OpenAlexaboutno aff

Bibliographic record

VenueCarleton University's Institutional Repository (MacOdrum Library, Carleton University) · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectual propertyStakeholderVariety (cybernetics)Foundation (evidence)Order (exchange)Property rightsPublic domainTraditional knowledge
DOInot available

Abstract

fetched live from OpenAlex

Intellectual Property Management encompasses creation, protection, and exploitation of intellectual property rights (IPRs) such as patents that play a critical role in research and development of intensive industries. Patent rights are known to provide significant benefits as they can be sold or licensed and form foundation for making, using, and selling industry-leading products, processes, and services. In order to obtain valid patent rights, however, basic knowledge of certain critical issues is considered essential among stakeholders. The authors assessed the basic knowledge of proper record keeping practices, ownership, and public disclosure among public and private sector organizations of various sizes across Canada in a variety of industries. They found that respondents had good knowledge of proper record keeping practices, assigning ownership of patent rights to the employers, and excellent knowledge of what constitutes a public disclosure. However, they had poor knowledge of what does not constitute a public disclosure and duration of the public disclosure grace period. The authors provided recommendations for implementing organizational processes for further educating stakeholders in obtaining valid patent rights for commercialization.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient 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 score0.673
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0010.012
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.099
GPT teacher head0.189
Teacher spread0.090 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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