Gold Nanoparticle Smartphone Platform for Diagnosing Urinary Tract Infections
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
Current urinary tract infection (UTI) diagnostic methods are slow or provide limited information, resulting in prescribing antibiotic therapy before bacterial pathogen identification. Here, we adapted a gold nanoparticle colorimetric approach and developed a smartphone platform for UTI detection. We show the parallel identification of five major UTI pathogens at clinically relevant concentrations of 105 bacteria/mL using bacteria-specific and universal probes. We validated the diagnostic technology using 115 positive and 19 negative samples from patients with Escherichia coli, Proteus mirabilis, and Klebsiella pneumoniae infections. The assay successfully identified the infecting pathogen (specificity: >98% and sensitivity: 51–73%) in 3 h. Our platform is faster than culturing and can wirelessly store and transmit results at the cost of $0.38 per assay.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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