Intracellular Growth of Bacterial Pathogens: The Role of Secreted Effector Proteins in the Control of Phagocytosed Microorganisms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Of the 56 million deaths reported worldwide in 2012, approximately 15 million are directly related to infectious diseases (1). The majority of annual deaths are related to bacterial infections such as tuberculosis, yellow and typhoid fever, cholera, shigellosis, pneumonia, etc. (1). Morbidity and mortality rates are highest in developing countries, where large numbers of infants and children count among the victims (2). In developed nations, infectious disease mortality falls most heavily on indigenous and disadvantaged minorities (3). The control of bacterial infectious diseases worldwide is an important task. Although antibiotics revolutionized the treatment of bacterial infections, increased resistance and the emergence of multidrug-resistant strains increasingly reduce their efficacy. This trend promotes an urgent need for better understanding of bacterial pathogenicity and resistance mechanisms, which will assist novel therapeutic and vaccination strategies.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it