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Record W2012856960 · doi:10.7202/042817ar

Droit d'auteur et logiciel

2005· article· en· W2012856960 on OpenAlexvenueaboutno aff
Denis Buron

Bibliographic record

VenueLes Cahiers de droit · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsnot available
Fundersnot available
KeywordsFirmwareTask (project management)FlowchartComputer scienceCreativitySoftwareWork (physics)Computer securityLawPolitical scienceProgramming languageManagementEngineeringEconomicsOperating system

Abstract

fetched live from OpenAlex

Under the present Canadian Copyright Act, it appears that protection is granted to computer programs, or software, as well as to flowcharts and firmware, or chips, whithout any relevant distinction. But the real problem is one of evidence. As a matter of fact, no layman can be expected to appreciate correctly a reproduction of a substantial part of a program where even experts are facing a troublesome task. New rules of evidence should be contemplated, based on behavior, since it is easier for the defendant to show that he did exercise creativity than for the plaintif to sustain that his work has been copied. That is especially important, considering that copyright seems to be the only answer for such badly needed protection.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.196
Threshold uncertainty score0.585

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.004
Scholarly communication0.0090.004
Open science0.0020.002
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.1750.047

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 head0.021
GPT teacher head0.271
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2005
Admission routes2
Has abstractyes

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