Comparison of sample pretreatments used to distinguish between infectious and non-infectious foodborne viruses by RT-qPCR
Bibliographic record
Abstract
), magnetic silica beads and centrifugal filter using HAV or HuNoV inactivated by heat, pulsed light, or sodium hypochlorite (NaOCl). PMAxx completely or nearly eliminated (3.96 ± 1.24 log gc) the RT-qPCR signal of HAV inactivated at 100°C for 10 min. Pretreatments could not reduce significantly RT-qPCR signal of HAV after pulsed light (0.74 ± 0.36 log gc) and NaOCl (0.24 ± 0.14 log gc) inactivation. Enzymatic treatments did not improve the results obtained with PMAxx. The exudate of raspberry, strawberry or oyster used as food matrices needed dilution by at least tenfold for PMAxx to to yield results comparable to virions without a food matrix. Overall, PMAxx shows good potential to discriminate between infectious and non-infectious despite some remaining limitations.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".