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Record W2105146758

Uneasy Fit: Software Patents and the Duty of Disclosure in Patent Law

2010· article· en· W2105146758 on OpenAlexaffabout
Robert J. Tomkowicz

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldComputer Science
TopicLaw, AI, and Intellectual Property
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSoftwareDutyMonopolyComputer scienceSource codeSoftware engineeringPatent lawPatent visualisationSoftware developmentLawIntellectual propertyData sciencePolitical scienceOperating systemEconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the duty of disclosure in patent law and discusses the potential insufficiency of disclosing a computer program’s functionality in patent applications for certain categories of software – applications working on closed platforms. In Canada, software patents are generally issued without disclosure of the software source code. Present examination of disclosure in software patent applications focuses solely on the ability of computer programmers to write software based on its functional description, which raises profound questions about sufficiency of disclosure in those applications.The problem of insufficient disclosure in software patent applications poses serious questions about the validity of a number of software patents already granted and should be resolved without delay. This paper recommends broader examination of software patent applications by ensuring that the software’s disclosure is sufficient to replicate the software’s functionality in the environment in which it functions during patent monopoly. Such analysis will often lead to a conclusion requiring disclosure of the software source code in patent applications.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.211
Teacher spread0.195 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2010
Admission routes2
Has abstractyes

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