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Record W4388496476 · doi:10.1016/j.tibs.2023.10.002

Dissecting the biophysics and biology of intrinsically disordered proteins

2023· article· en· W4388496476 on OpenAlexfundno aff
Priya R. Banerjee, Alex S. Holehouse, Richard W. Kriwacki, Paul Robustelli, Hao Jiang, Alexander I. Sobolevsky, Jennifer Hurley, Joshua T. Mendell

Bibliographic record

VenueTrends in Biochemical Sciences · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesNational Cancer InstituteAmerican Lebanese Syrian Associated CharitiesNational Institutes of HealthCancer Prevention and Research Institute of TexasUniversity of VirginiaYork UniversityDartmouth CollegeUniversity of California, San DiegoNational Institute on AgingSt. Jude Children's Research HospitalUniversity of Texas Health Science Center at San AntonioUniversity of Texas Southwestern Medical CenterCarnegie Institution of WashingtonState University of New YorkWelch FoundationUniversity of PennsylvaniaWashington University in St. LouisNew York UniversityRensselaer Polytechnic InstituteColumbia UniversityHoward Hughes Medical InstituteNational Science Foundation
KeywordsIntrinsically disordered proteinsComputational biologyBiologyCell biologyNeuroscienceBiophysics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.251

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.039
GPT teacher head0.353
Teacher spread0.314 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations21
Published2023
Admission routes1
Has abstractno

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