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Record W2594019989 · doi:10.3390/microorganisms5010009

Microbial Biofilms and Chronic Wounds

2017· review· en· W2594019989 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMicroorganisms · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsBiofilmDebridement (dental)Context (archaeology)MicrobiologyVirulenceMedicineImmune systemAntimicrobialChronic woundBiologyWound healingImmunologyBacteriaSurgery

Abstract

fetched live from OpenAlex

Background is provided on biofilms, including their formation, tolerance mechanisms, structure, and morphology within the context of chronic wounds. The features of biofilms in chronic wounds are discussed in detail, as is the impact of biofilm on wound chronicity. Difficulties associated with the use of standard susceptibility tests (minimum inhibitory concentrations or MICs) to determine appropriate treatment regimens for, or develop new treatments for use in, chronic wounds are discussed, with alternate test methods specific to biofilms being recommended. Animal models appropriate for evaluating biofilm treatments are also described. Current and potential future therapies for treatment of biofilm-containing chronic wounds, including probiotic therapy, virulence attenuation, biofilm phenotype expression attenuation, immune response suppression, and aggressive debridement combined with antimicrobial dressings, are described.

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)0.000
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 score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.033
GPT teacher head0.302
Teacher spread0.269 · 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