CRISPR technology incorporating amplification strategies: molecular assays for nucleic acids, proteins, and small molecules
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
-cleavage activity of Cas12 and Cas13, and unwinding and nicking ability of Cas9. Integrating a CRISPR-Cas system after nucleic acid amplification improves detection specificity due to RNA-guided recognition of specific sequences of amplicons. Incorporating CRISPR-Cas before nucleic acid amplification enables enrichment of rare and low-abundance nucleic acid targets and depletion of unwanted abundant nucleic acids. Unwinding of dsDNA to ssDNA using CRISPR-Cas9 at a moderate temperature facilitates techniques for achieving isothermal exponential amplification of nucleic acids. A combination of CRISPR-Cas systems with functional nucleic acids (FNAs) and molecular translators enables the detection of non-nucleic acid targets, such as proteins, metal ions, and small molecules. Successful integrations of CRISPR technology with nucleic acid amplification techniques result in highly sensitive and rapid detection of SARS-CoV-2, the virus that causes the COVID-19 pandemic.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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