A personal history of research on microbial biofilms and biofilm infections
Bibliographic record
Abstract
The observation of aggregated microorganisms surrounded by a self-produced matrix adhering to surfaces or located in tissues or secretions is as old as microbiology, with both Leeuwenhoek and Pasteur describing the phenomenon. In environmental and technical microbiology, biofilms were already shown 80–90 years ago to be important for biofouling on submerged surfaces, e.g. ships. The concept of biofilm infections and their importance in medicine is, however, 40 years old and was started by Jendresen's observations of aquired dental pellicles and my own observations of heaps of Pseudomonas aeruginosa cells in sputum and lung tissue from chronically infected cystic fibrosis patients. The term biofilm was introduced into medicine in 1985 by Costerton. In the following decades, it became obvious that biofilm infections are widespread in medicine, and their importance is now generally accepted. The words ‘biofilms’ and biofilm infections has only been used in medicine for 30 years, but the phenomenon was detected already by Leeuwenhoek and Pasteur and by environmental microbiologists in the 1920s and 30s.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.015 |
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".