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Record W3018720493 · doi:10.1128/iai.00230-20

Cathelicidins Mitigate Staphylococcus aureus Mastitis and Reduce Bacterial Invasion in Murine Mammary Epithelium

2020· article· en· W3018720493 on OpenAlexafffund
Paloma A. Cavalcante, Cameron G. Knight, Yi-Lin Tan, A.P.A. Monteiro, Herman W. Barkema, Eduardo R. Cobo

Bibliographic record

VenueInfection and Immunity · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsStaphylococcus aureusBiologyMastitisMicrobiologyEpitheliumMammary glandStaphylococcal infectionsImmunologyBacteria

Abstract

fetched live from OpenAlex

Staphylococcus aureus , an important cause of mastitis in mammals, is becoming increasingly problematic due to the development of resistance to conventional antibiotics. The ability of S. aureus to invade host cells is key to its propensity to evade immune defense and antibiotics. This study focuses on the functions of cathelicidins, small cationic peptides secreted by epithelial cells and leukocytes, in the pathogenesis of S. aureus mastitis in mice.

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 head0.035
GPT teacher head0.231
Teacher spread0.197 · 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

Citations9
Published2020
Admission routes2
Has abstractyes

Explore more

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