Nucleic acid amplification-based diagnosis of respiratory virus 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
The appearance of eight new respiratory viruses in the human population in the past 9 years, including two new pandemics (SARS coronavirus in 2003 and swine-origin influenza A/H1N1 in 2009), has tested the ability of virology laboratories to develop diagnostic tests to identify these viruses. Nucleic acid amplification tests (NATs) that first appeared two decades ago have been developed for both conventional and emerging viruses and now form the backbone of the clinical laboratory. NATs provide fast, accurate and sensitive detection of respiratory viruses and have significantly increased our understanding of the epidemiology of these viruses. Multiplex PCR assays have been introduced recently and several commercial tests are now available. The final chapter in the evolution of respiratory virus diagnostics will be the addition of allelic discrimination and detection of single nucleotide polymorphisms associated with antiviral resistance to multiplex assays. These resistance assays together with new viral load tests will enable clinical laboratories to provide physicians with important information for optimal treatment of patients.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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