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Record W2073820022 · doi:10.1017/s1466252310000149

Biofilm formation in bacterial pathogens of veterinary importance

2010· review· en· W2073820022 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnimal Health Research Reviews · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBiofilmMicrobiologyBacteriaAntibioticsBiology

Abstract

fetched live from OpenAlex

Bacterial biofilms are structured communities of bacterial cells enclosed in a self-produced polymer matrix that is attached to a surface. Biofilms protect and allow bacteria to survive and thrive in hostile environments. Bacteria within biofilms can withstand host immune responses, and are much less susceptible to antibiotics and disinfectants when compared with their planktonic counterparts. The ability to form biofilms is now considered a universal attribute of micro-organisms. Diseases associated with biofilms require novel methods for their prevention, diagnosis and treatment; this is largely due to the properties of biofilms. Surprisingly, biofilm formation by bacterial pathogens of veterinary importance has received relatively little attention. Here, we review the current knowledge of bacterial biofilms as well as studies performed on animal pathogens.

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.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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)0.0000.000

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 head0.278
GPT teacher head0.477
Teacher spread0.199 · 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