The impact of simultaneous infections on phage-host ecology
Bibliographic record
Abstract
Phages use bacterial host resources to replicate, intrinsically linking phage and host survival. To understand phage dynamics, it is essential to understand phage-host ecology. A key step in this ecology is infection of bacterial hosts. Previous work has explored single and multiple, sequential infections. Here we focus on the theory of simultaneous infections, where multiple phages simultaneously attach to and infect one bacterial host cell. Simultaneous infections are a relevant infection dynamic to consider, especially at high phage densities when many phages attach to a single host cell in a short time window. For high bacterial growth rates, simultaneous infection can result in bi-stability: depending on initial conditions phages go extinct or co-exist with hosts, either at stable densities or through periodic oscillations of a stable limit cycle. This bears important consequences for phage applications such as phage therapy: phages can persist even though they cannot invade. Consequently, through spikes in phage densities it is possible to infect a bacterial population even when the phage basic reproductive number is less than one. In the regime of stable limit cycles, if timed right, only small densities of phage may be necessary.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".