MétaCan
Menu
Back to cohort
Record W2341292252 · doi:10.1002/1873-3468.12175

Rapid amyloid fibril formation by a winter flounder antifreeze protein requires specific interaction with ice

2016· letter· en· W2341292252 on OpenAlexafffund
André Dubé, Cindy Leggiadro, K. Vanya Ewart

Bibliographic record

VenueFEBS Letters · 2016
Typeletter
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsNational Research Council CanadaDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWinter flounderAntifreeze proteinAntifreezeIce formationChemistryAmyloid (mycology)Amyloid fibrilBiophysicsIce crystalsFlounderBiochemistryBiologyFish <Actinopterygii>Amyloid βGeologyFisheryOrganic chemistryInternal medicineMeteorology

Abstract

fetched live from OpenAlex

A typically α-helical antifreeze protein (wflAFP-6) from winter flounder, Pseudopleuronectes americanus, forms amyloid fibrils during freezing. In this study, the effects of distinct components of the freezing process were examined. Freezing of wflAFP-6 in the presence of template ice was shown to be necessary for rapid conversion to an amyloid conformation. Neither subfreezing temperature nor phase change was sufficient. Thus, specific interaction with the ice surface was essential. The ice-induced formation of amyloid appeared to be unique to this helical antifreeze, it required high concentrations of protein and it occurred over a range of pH values. These results define a method for rapid formation of amyloid by wflAFP-6 on demand under physiological conditions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.203
Teacher spread0.185 · 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 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

Citations3
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueFEBS LettersSame topicPhysiological and biochemical adaptationsFrench-language works237,207