Phage Production and Maintenance of Stocks, Including Expected Stock Lifetimes
Bibliographic record
Abstract
In microbiology, preservation of an archival stock or a "master stock" of a given microorganism is essential for many reasons including scientific research, conservation of the genetic resources and providing the foundation for several biotechnological processes. The objective is to preserve the initial characteristics of the microorganism and to avoid the genetic drift that occurs when the organism is maintained indefinitely in an actively growing state. The same holds true in phage biology and it is of particular interest when a collection of phages is to be maintained. The aim of this chapter is to provide phage biologists with general procedures to prepare and maintain bacteriophage stocks on a long-term basis. The protocols described below should be considered as general guidelines because although many phages and bacterial strains can be propagated and stored in these conditions, specific media and/or growth and storage conditions must be evaluated for each phage and bacterium. Since it was not the scope of this chapter to provide an exhaustive list of these particular conditions, we instead highlighted the main factors affecting phage amplification and storage. We hope this will help phage biologists to develop their own strategies for their preferred phages.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.008 |
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".