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Record W3092439892 · doi:10.47670/wuwijar201821fco

Infringement Cases of Intellectual Properties

2018· article· en· W3092439892 on OpenAlexaff
Faith Caiudo Orillaza

Bibliographic record

VenueWestcliff International Journal of Applied Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsWycliffe College
Fundersnot available
KeywordsCopyingPatent infringementEntitlement (fair division)Copyright infringementDamagesPlaintiffLawBusinessIntellectual propertyMisappropriationEstoppelExclusive rightLaw and economicsPolitical scienceEconomicsDoctrine

Abstract

fetched live from OpenAlex

Intellectual properties are collected ideas and concepts that originated from different sources, such as an individual or company. The entity who carries the title of being the owner of the idea has the sole right in copying or duplicating his own concepts. Despite entitlement of ownership, many people step across the perimeter of the boundaries set by the author. This type of violation is called copyright infringement, where ideas are copied and used without the approval of the originator. The focus of this paper is to discuss some of the companies who are involved in infringement issues like Napster, Bertelsmann, and Blackberry. They were sued by Metallica, Electric and Musical Industries (EMI) and Universal Studios respectively. Additionally, making use of one’s invention without the permission of the inventor is called patent infringement. It violates the exclusive rights given by the federal government to the maker of the innovation. NTP Inc., a company with no technology of its own and Oxbo both violated patent rights and were sued by Research in Motion (RIM) and H&S Manufacturing respectively. Each of these cases will be discussed in detail considering various facts, violations, court rulings, and financial damages.

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)0.002
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.374
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.348
GPT teacher head0.339
Teacher spread0.009 · 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
Published2018
Admission routes1
Has abstractyes

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