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Record W1563864018 · doi:10.1002/jez.b.22551

The role of domain shuffling in the evolution of signaling networks

2013· review· en· W1563864018 on OpenAlexaff
Raphaël B. Di Roberto, Sergio G. Peisajovich

Bibliographic record

VenueJournal of Experimental Zoology Part B Molecular and Developmental Evolution · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsShufflingNoveltyCognitive scienceDomain (mathematical analysis)Evolutionary biologyBiological evolutionBiologyComputer scienceEpistemologyPhilosophyGeneticsPsychology

Abstract

fetched live from OpenAlex

In a seminal paper entitled "Evolution and Tinkering," François Jacob affirmed that: "Novelties come from previously unseen association of old material. To create is to recombine" [Jacob F. (1977) Science 196:1161-1166]. In the 35 years that have passed since Jacob's insight, we have amassed enough data to actually shed light on many of the molecular mechanisms that enable evolution to create novelty by simply recombining what existed already. In this review, we will succinctly discuss the role that the recombination of protein domains has in the evolution of signaling networks, drawing from examples provided by diverse disciplines, including bioinformatics, systems and synthetic biology, and laboratory evolution.

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)0.001
metaresearch head score (Gemma)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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
GenreReview

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

Citations24
Published2013
Admission routes1
Has abstractyes

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