Bibliographic record
Abstract
The microbial ecology of caries is complex and incorporates mechanisms common to the natural colonization of the host and to plaque accumulation at sites that do not develop caries lesions. It is not simply accumulation of plaque in the oral cavity but also the ecology of oral bacteria among the host population and the ecology of organisms in the lesion. In these three habitats odontopathogens and other oral bacteria can undergo genotypic change, which may produce phenotypes more virulent or better able to survive specific evironments. Adaptation and response to stress will also enhance bacterial survival and selection. Therefore, in these habitats diversity is generated and this, coupled with adaptation, provides strains that are selected to be best suited to specific environments, including cariogenic environments. In this way odontopathogens may be selected and become more numerous among hosts in a population. The most common ecological mechanism associated with caries is bacterial succession, and dominance of the plaque community by mutans streptococci. However caries is the outcome of interactions within the plaque community, host physiology, diet, fluoride, pH and the nature of the tooth enamel, and dominance by mutans streptococci does not always produce a lesion. Caries can be reduced by bacteria that degrade lactate or produce base from urea and salivary peptides, while other bacteria, including a group of 'low pH' streptococci could lower the pH of plaque, and produce enamel demineralization. In addition, the plaque biofilm not only serves as a habitat but includes in its structure a fluid phase (plaque fluid) and a matrix that have a direct influence on the physiology of plaque bacteria and the formation of a lesion. Given the complexity of the microbial ecology of caries even with the elimination of mutans streptococci caries would most likely persist, albeit at a significantly reduced level.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".