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Record W2949333610 · doi:10.1177/1176934319855937

Using Pseudoenzymes to Probe Evolutionary Design Principles of Enzymes

2019· letter· en· W2949333610 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEvolutionary Bioinformatics · 2019
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsMcGill University
Fundersnot available
KeywordsEvolutionary physiologyComputer scienceEvolutionary biologyEvolutionary algorithmEvolutionary ecologyComputational biologyBiologyBiochemical engineeringEcologyArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

Enzymes are governed by unique evolutionary design principles as their catalytic sites were shown to induce long-range evolutionary conservation gradients. We have recently used a comparative bioinformatics approach to disentangle structural determinants from other possible determinants of the evolutionary conservation gradients. The approach is based on comparing the evolutionary patterns of enzymes to those of pseudoenzymes with the same tertiary structure where the catalytic functionality is turned off. This approach provides a way to evaluate several hypotheses regarding the origin of the observed evolutionary conservation gradient in enzymes. The conclusions from such comparative analyses are important for a better understanding of the unique evolutionary design principles of enzymes, which can in turn potentially guide the design of new and improved enzymes.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0010.000
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 head0.034
GPT teacher head0.245
Teacher spread0.211 · 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