MétaCan
Menu
Back to cohort
Record W2742643337 · doi:10.1126/sciadv.1701440

Structure of a 1.5-MDa adhesin that binds its Antarctic bacterium to diatoms and ice

2017· article· en· W2742643337 on OpenAlexafffund
Shuaiqi Guo, Corey A. Stevens, Tyler D. R. Vance, Luuk L. C. Olijve, Laurie A. Graham, Robert L. Campbell, Saeed Rismani Yazdi, Carlos Escobedo, Maya Bar Dolev, Victor Yashunsky, Ido Braslavsky, David N. Langelaan, Steven P. Smith, John S. Allingham, Ilja K. Voets, Peter L. Davies

Bibliographic record

VenueScience Advances · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsQueen's University
FundersEuropean Research CouncilNatural Sciences and Engineering Research Council of CanadaQueen's UniversityHanyang UniversityNederlandse Organisatie voor Wetenschappelijk OnderzoekBrookhaven National LaboratoryCanadian Institutes of Health ResearchCanadian Light Source
KeywordsBacterial adhesinPeriplasmic spaceBacteriaSecretionBacterial outer membraneBiologyMicrobiologyCell biologySignal peptideEscherichia coliBiochemistryPeptide sequenceGeneGenetics

Abstract

fetched live from OpenAlex

to project the adhesion regions RIII and RIV into the medium. RIII contains ligand-binding domains that join diatoms and bacteria together in a mixed-species community on the underside of sea ice where incident light is maximal. RIV is the ice-binding domain, and the terminal RV domain contains several "repeats-in-toxin" motifs and a noncleavable signal sequence that target proteins for export via the type I secretion system. Similar structural architecture is present in the adhesins of many pathogenic bacteria and provides a guide to finding and blocking binding domains to weaken infectivity.

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 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 score0.469
Threshold uncertainty score0.613

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 studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.276
Teacher spread0.266 · 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

Citations105
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueScience AdvancesSame topicBacteriophages and microbial interactionsFrench-language works237,207