Bibliographic record
Abstract
Bacterial biofilms are structured clusters of bacterial cells enclosed in a self-produced polymer matrix that are attached to a biotic or abiotic surface. This structure protects bacteria from hostile environmental conditions. There are also accumulating reports about bacterial aggregates associated but not directly adherent to surfaces. Interestingly, these bacterial aggregates exhibit many of the same phenotypes as surface-attached biofilms. Surface-attached biofilms as well as non-attached aggregates are ubiquitous and found in a wide variety of natural and clinical settings. This strongly suggests that biofilm/aggregate formation is important at some steps in the bacterial lifecycle. Biofilm/aggregate formation might therefore be important for some bacterial species for persistence within their host or their environment, while for other bacterial species it might be more important for persistence in the environment between infection of different individuals or even between infection of different hosts (humans or animals). This is strikingly similar to the One Health concept which recognizes that the health and well-being of humans, animals and the environment are intricately linked. We would like to propose that within this One Health concept, the One Biofilm concept also exists, where biofilm/aggregate formation in humans, animals and the environment are also intricately linked. Biofilm/aggregates could represent the unifying factor underneath the One Health concept. The One Biofilm concept would support that biofilm/aggregate formation might be important for persistence during infection but might as well be even more important for persistence in the environment and for transmission between different individuals/different 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".