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Record W2148571098 · doi:10.2741/3019

Exploring energy landscapes of protein folding and aggregation

2008· review· en· W2148571098 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

VenueFrontiers in bioscience · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsUniversité du Québec à MontréalUniversité de Montréal
Fundersnot available
KeywordsEnergy landscapeProtein foldingFolding (DSP implementation)Protein aggregationChemistryBiophysicsComputer scienceBiologyBiochemistryEngineering

Abstract

fetched live from OpenAlex

Human diseases, such as Alzheimer's and Creutzfeldt-Jakob's are associated with misfolding and aggregation of specific proteins into amyloid fibrils sharing a generic cross-beta structure. The self-assembly process is complex, but once a nucleus is formed, rapid fibril formation occurs. Insight into the structures of the oligomers during the lag phase, varying between hours and days, is very difficult experimentally because these species are transient, and numerically using all-atom molecular dynamics because the time scale explored is on the order of 10-100 ns. It is therefore important to develop simplified protein models and alternative methods to sample more efficiently the conformational space. In the past few years, we have developed the activation-relaxation technique (ART nouveau) coupled to the OPEP coarse-grained force field. This review reports the application of ART-OPEP on protein folding and aggregation.

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 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 score0.998
Threshold uncertainty score0.599

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 integrity0.0000.000
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 head0.032
GPT teacher head0.254
Teacher spread0.222 · 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