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A Procedure to Test Biofilm Formation Capacities of Listeria Monocytogenes Strains Under Conditions Simulating Natural Meat Processing Conditions v1

2025· preprint· en· W4409545230 on OpenAlexfundno aff
Diana Margaret Soosai, Beverly Phipps‐Todd, Min Lin, Burton W. Blais, Hongsheng Huang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicListeria monocytogenes in Food Safety
Canadian institutionsnot available
FundersCanadian Food Inspection Agency
KeywordsListeria monocytogenesBiofilmFood scienceListeriaMicrobiologyChemistryBiochemical engineeringBiologyBacteriaEngineering

Abstract

fetched live from OpenAlex

Biofilm formation is believed to be one of the mechanisms that enables Listeria monocytogenes, a food-borne bacterial pathogen, to persist in food processing plants. It is important to determine the differential abilities of biofilm formation of various L. monocytogenes strains under natural conditions for gaining insights into this mechanism and for developing effective mitigation strategies. The protocol presented here outlines an in vitro biofilm assay developed in our laboratory to detect biofilm formation in L. monocytogenes strains. This assay uses a standard crystal violet biofilm assay in a novel model (in-house prepared Beef Broth, 12ºC), closely simulating natural meat processing environments. The biofilm formation is measured using optical density values and confirmed morphologically using inverted microscopy and scanning electron microscopy.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.075
GPT teacher head0.360
Teacher spread0.285 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same topicListeria monocytogenes in Food SafetyFrench-language works237,207