Bibliographic record
Abstract
In recent years, numerous bacterial species have developed antibiotic resistance due to the overuse of antibiotics in the home, health care setting, and in agriculture. Alternative methods of treatment, including phage therapy (PT), have been proposed as solutions to this problem. PT is showing promise as an alternative method of treatment against the bacteria methicillin-resistant Staphylococcus aureus (MRSA). MRSA is a virulent and antibiotic resistant bacterium capable of causing infections of the skin, respiratory system, and various other body systems. In this research proposal, we propose investigating the use of the Staphylococcal bacteriophage (phage) GH15 as a therapeutic agent against MRSA infections due to its broad host range, its lack of bacterial virulence genes, and its strong ability to lyse various strains of MRSA. Specifically, we propose to evaluate the tail fibre genes of GH15 contributing to the phage’s host range, in addition to the ability of the phage to induce antiphage humoral immune responses in human cells, in the interest of exploring GH15 as a therapeutic agent for use in PT, specifically against MRSA.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".