Molecular epidemiology of Pseudomonas Aeruginosa
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
Pseudomonas aeruginosa is a serious opportunistic pathogen in certain compromised hosts, such as those with cystic fibrosis, thermal burns and cancer. It also causes less severe noninvasive disease, such as otitis externa and hot tub folliculitis, in normal hosts. P. aeruginosa is phenotypically very unstable, particularly in patients with chronic infection. Phenotypic typing techniques are useful for understanding the epidemiology of acute infections, but they are limited by their discriminatory power and by their inability to group isolates that are phenotypically unrelated but genetically homologous. Molecular typing techniques, developed over the past decade, are highly discriminatory and are useful for typing strains from patients with chronic infection where the bacterial phenotype is unstable; this is particularly true in cystic fibrosis, where patients often are infected with the same strain for several decades, but the bacteria undergo phenotypic alteration. Molecular typing techniques, which have proven useful in typing P. aeruginosa for epidemiological purposes, include pulsed field gel electrophoresis, restriction fragment length polymorphic DNA analysis, random amplified polymorphic DNA analysis, repetitive extrapalindromic PCR analysis, and multilocus sequence typing. These methods are generally only available in specialized laboratories, but they should be used when data from phenotypic typing analysis are ambiguous or when phenotypic methods are unreliable, such as in cystic fibrosis.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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