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Record W130778510

'Secondary' Evidence of Obviousness is Not Secondary

2012· article· en· W130778510 on OpenAlexaff
Norman Siebrasse

Bibliographic record

VenueSSRN Electronic Journal · 2012
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsUniversity of New BrunswickUniversity of Fredericton
Fundersnot available
KeywordsRules of evidenceAppealExpert witnessLawFederal Rules of EvidenceCircumstantial evidenceScientific evidenceWitnessHigh CourtEmpirical evidencePsychologyPolitical scienceEpistemologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

In assessing whether a claimed invention is obvious, a court will hear evidence from expert witnesses as to the knowledge and state of mind of a hypothetical skilled person at the relevant time, then “assume the mantle” of that person and assess whether the invention would have been obvious to him or her. The court may also consider the circumstances of the invention and its reception, most prominently whether there was a long-felt need and commercial success. This type of evidence is now commonly know as “secondary” evidence. The UK Court of Appeal has said that secondary evidence is substantively secondary to the evidence of expert witnesses, while in contrast in US law failure to consider secondary evidence is an error of law. This note argues that the view that so-called secondary evidence is inherently of lesser importance than the evidence of expert witness is wrong as a matter of policy.

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)0.043
metaresearch head score (Gemma)0.225
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.043
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.225
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0040.030
Scholarly communication0.0110.022
Open science0.0040.009
Research integrity0.0180.013
Insufficient payload (model declined to judge)0.0150.002

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 head0.061
GPT teacher head0.426
Teacher spread0.365 · 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 designTheoretical or conceptual
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
Published2012
Admission routes1
Has abstractyes

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