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Record W4407798166 · doi:10.1093/fqsafe/fyaf008

Interspecies and intraspecies ‘Talk’ shape the bacterial biofilms

2025· article· en· W4407798166 on OpenAlex
Lou Yiyang, Ziqi Liu, Qiyi Zhang, Lujie Zhang, Xinyu Liao, Yang Tian, Donghong Liu, Xiaonan Lu, Juhee Ahn, Tian Ding, Jinsong Feng

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

VenueFood Quality and Safety · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsMcGill University
FundersNatural Science Foundation of Zhejiang Province
KeywordsBiofilmBiologyMicrobiologyBacteriaGenetics

Abstract

fetched live from OpenAlex

Abstract Bacteria pretend to organize into complex, multicellular structures known as biofilms, which enable survival and adaptation in dynamic environments. Bacterial biofilms serve diverse functions, including providing structural stability, directing metabolic adaptations, and facilitating bacterial expansion and nutrient acquisition. In natural environments, biofilms are predominantly formed by diverse multispecies bacteria. The formation of multispecies biofilms is a dynamic process shaped by intricate bacterial interactions, encompassing both cooperative and antagonistic behaviors. These interactions are mediated by signaling molecules that facilitate cell-to-cell communications, influenced by the spatiotemporal heterogeneity of the extracellular polymeric substance matrix and biofilm architecture. This review synthesizes recent advances in understanding bacterial interactions within biofilms, focusing on mediating metabolites, underlying mechanisms, and their implications for the process of biofilm development. These insights offer a foundation for developing strategies to manipulate microbial communities and control biofilm-related challenges.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.997

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.268
Teacher spread0.243 · 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