Relationship between Planktonic and Sessile Cells as They Relate to Biofilm Growth
Bibliographic record
Abstract
Abstract Microbially influenced corrosion (MIC) is a process whereby microbial cells living in an exopolymer matrix, known as a biofilm, induce corrosion of the associated surface. The risk of MIC within a system is usually assessed by measuring planktonic (free-floating) cells, which is assumed to approximate the biofilm-associated cells (sessile) cells. This work aimed to determine the accuracy of this industry-practiced approach of assessing MIC risk from planktonic cell counts. Planktonic and sessile cell counts of two single species cultures, one of an aerobe (Pseudomonas fluorescens) and one of an anaerobe (Geoalkalibacter subterraneus), both of which have been associated with MIC, were monitored in a growth curve test to determine how planktonic and sessile cell counts relate during the initial stages of biofilm formation. The results indicate two factors govern biofilm initiation of the tested species. Firstly, a minimum planktonic cell density is required and secondly, a minimum exposure time of the surface are both required prior to biofilm initiation and the onset of internal corrosion of carbon-steel pipelines. Both these factors affect biofilm formation in a species specific manner.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".