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The Semantics of the Modular Architecture of Protein Structures

2015· review· en· W2419164853 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

VenueCurrent Protein and Peptide Science · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsDalhousie University
Fundersnot available
KeywordsModularity (biology)Computer scienceModular designEvolvabilityArchitectureSemantics (computer science)Context (archaeology)Function (biology)Domain (mathematical analysis)HierarchyTheoretical computer scienceInferenceSelection (genetic algorithm)Artificial intelligenceProgramming languageBiologyMathematicsEvolutionary biology

Abstract

fetched live from OpenAlex

Protein structures can be conceptualized as context-aware self-organizing systems. One of its emerging properties is a modular architecture. Such modular architecture has been identified as domains and defined as its units of evolution and function. However, this modular architecture is not exclusively defined by domains. Also, the definition of a domain is an ongoing debate. Here we propose differentiating structural, evolutionary and functional domains as distinct concepts. Defining domains or modules is confounded by diverse definitions of the concept, and also by other elements inherent to protein structures. An apparent hierarchy in protein structure architecture is one of these elements, where lower level interactions may create noise for the definition of higher levels. Diverse modularity-molding factors such as folding, function, and selection, can have a misleading effect when trying to define a given type of module. It is thus important to keep in mind this complexity when defining modularity in protein structures and interpreting the outcome modularity inference approaches.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.024
GPT teacher head0.319
Teacher spread0.295 · 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