In Vitro Assessment of Biofilm Formation by Soil‐ and Plant‐Associated Microorganisms
Bibliographic record
Abstract
This chapter reviews examples of laboratory methods successfully used for cultivating microbial biofilms in vitro. For each in vitro biofilm reactor, the system's strengths and weaknesses are discussed and examples of protocols, diagrams, or schematics provided. The chapter also deals with a summary of the methods to describe plant-associated microbial biofilms. Some experiments use a microorganism in pure culture, while others use a defined microcosm, or an unpurified sampling. Once the experimental goals and objectives of biofilm culturing methods are determined, a second consideration in selecting an in vitro biofilm method is the cost and consistency or reproducibility of each system. When one considers the diversity of biofilm reactors that have been engineered and utilized, it is interesting that relatively few have been used to characterize plant-associated biofilms. The first plant-pathogenic biofilm characterized in vitro was that of Xylella fastidiosa, the causal agent of vascular diseases in a number of plant hosts.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".