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Record W2150964333 · doi:10.1085/jgp.200609633

Importance of Hydration and Dynamics on the Selectivity of the KcsA and NaK Channels

2007· review· en· W2150964333 on OpenAlexafffund
Sergei Y. Noskov, Benoı̂t Roux

Bibliographic record

VenueThe Journal of General Physiology · 2007
Typereview
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsUniversity of Calgary
FundersNational Institute of General Medical SciencesNational Institutes of HealthWestern Canada Research GridNational Centre for Supercomputing Applications
KeywordsKcsA potassium channelNAKSelectivityChemistryMolecular dynamicsIon channelIonBiophysicsChemical physicsComputational chemistryBiochemistryBiologyComputer scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Fundamental concepts governing ion selectivity in narrow pores are reviewed and the microscopic factors responsible for the lack of selectivity of the NaK channel, which is structurally similar to the K+-selective KcsA channel, are elucidated on the basis of all-atom molecular dynamics free energy simulations. The results on NaK are contrasted and compared with previous studies of the KcsA channel. Analysis indicates that differences in hydration of the cation in the pore of NaK is at the origin of the lack of selectivity of NaK.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.027
GPT teacher head0.265
Teacher spread0.238 · 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

Citations194
Published2007
Admission routes2
Has abstractyes

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