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Record W2783785722 · doi:10.1126/scitranslmed.aan4044

The antimicrobial peptide SAAP-148 combats drug-resistant bacteria and biofilms

2018· article· en· W2783785722 on OpenAlexaff
Anna de Breij, Martijn Riool, Robert A. Cordfunke, Nermina Malanović, Leonie de Boer, Roman I. Koning, E. Ravensbergen, Marnix Franken, Tobias van der Heijde, Bouke K. H. L. Boekema, Paulus H. S. Kwakman, Niels Kamp, A. El Ghalbzouri, Karl Lohner, Sebastian A. J. Zaat, Jan W. Drijfhout, Peter H. Nibbering

Bibliographic record

VenueScience Translational Medicine · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsAntimicrobialAntibioticsPeptideBacteriaMicrobiologyBiofilmDrugAntimicrobial peptidesRefractory (planetary science)MedicineChemistryPharmacologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

from wounded ex vivo human skin and murine skin in vivo. Together, these data demonstrate that SAAP-148 is a promising drug candidate in the battle against antibiotic-resistant bacteria that pose a great threat to human health.

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 score0.002
Threshold uncertainty score0.005

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.253
Teacher spread0.240 · 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

Citations537
Published2018
Admission routes1
Has abstractyes

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