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Record W2896494833 · doi:10.1007/s00232-018-0050-y

Understanding Conformational Dynamics of Complex Lipid Mixtures Relevant to Biology

2018· review· en· W2896494833 on OpenAlexaff
Ran Friedman, Syma Khalid, Camilo Aponte‐Santamaría, Elena Arutyunova, Marlon Becker, Kevin J. Boyd, Mikkel Hovden Christensen, João T. S. Coimbra, Simona Concilio, Csaba Daday, Floris J. van Eerden, Pedro Alexandrino Fernandes, Frauke Gräter, Davit Hakobyan, Andreas Heuer, Konstantina Karathanou, Fabian Keller, M. Joanne Lemieux, ‪Siewert J. Marrink, Eric R. May, Antara Mazumdar, Richard J Naftalin, Mónica Pickholz, Stefano Piotto, Peter Pohl, Peter J. Quinn, Maria J. Ramos, Birgit Schiøtt, Durba Sengupta, Lucia Sessa, Stefano Vanni, Talia Zeppelin, Valeria Zoni, Ana‐Nicoleta Bondar, Cármen Domene

Bibliographic record

VenueThe Journal of Membrane Biology · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversity of Alberta
FundersBiotechnology and Biological Sciences Research CouncilNational Institute of General Medical SciencesLundbeckfondenSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsPerspective (graphical)Dynamics (music)Membrane biologyHuman physiologyStructural biologyMolecular dynamicsChemistryBiophysicsComputational biologyPhysicsBiologyComputer scienceBiochemistryComputational chemistryArtificial intelligenceMembrane

Abstract

fetched live from OpenAlex

This is a perspective article entitled "Frontiers in computational biophysics: understanding conformational dynamics of complex lipid mixtures relevant to biology" which is following a CECAM meeting with the same name.

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)0.002
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
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.002

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 head0.097
GPT teacher head0.350
Teacher spread0.252 · 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

Citations46
Published2018
Admission routes1
Has abstractyes

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