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Record W4415855079 · doi:10.1093/jlb/lsaf026

Clades, classifications, and claims: evolution of organisms and their nomenclature in life science patents

2025· article· en· W4415855079 on OpenAlexaff
Nathan T. Jacobs

Bibliographic record

VenueJournal of Law and the Biosciences · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsGreenfield Research (Canada)
Fundersnot available
KeywordsExtant taxonNomenclatureTaxonomy (biology)Tree of life (biology)Three-domain systemField (mathematics)SystematicsModern evolutionary synthesis

Abstract

fetched live from OpenAlex

Organisms are complex biological entities that are less easily defined by specific structures or sequences than molecules, nucleic acids, and antibodies. Nor are they necessarily fixed in time or reproducible by repeatable methods, given their capacity for replication and mutation. Like organisms themselves, names and classifications also change over time as scientists better understand extant biodiversity. Taxonomy is the field of evolutionary biology concerned with classifying, naming, and identifying organisms, while phylogenetics concerns organisms' evolutionary history and relatedness. Here, I review the challenges evolution poses for patentees, using the examples of evolving influenza viruses and bacterial classifications, and Federal Circuit decisions relevant each issue. I conclude that careful consideration of organisms' evolutionary histories and the systematics underlying their classification in specification drafting allows patentees to: (i) mitigate the impact of scientific disagreement (such as the 'species problem' in microbiology) in claim construction; (ii) limit the effects of changing classifications on infringement analysis; (iii) describe generic categories of related organisms to encompass later-arising ones; and (iv) bolster compliance with the written description and enablement requirements of 35 U.S.C. § 112(a). Accordingly, patentees might address the challenges that evolutionary uncertainty poses for organism-centered patents by embracing these areas of evolutionary biology.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.049
GPT teacher head0.223
Teacher spread0.175 · 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
Published2025
Admission routes1
Has abstractyes

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