Specific detection by PCR of Streptococcus agalactiae in milk.
Bibliographic record
Abstract
The aim of this study was to develop a simple and specific method for direct detection of Streptococcus agalactiae from cow's milk. The method was based on polymerase chain reaction (PCR) using species-specific and universal primers derived from the 16S rRNA gene. The amplification product was verified by restriction endonuclease digest and sequencing. Specific identification was proven on a collection of 147 S. agalactiae isolates of bovine and human origin. In addition, 17 strains belonging to different bacterial species that potentially can be found in milk samples also tested negative. The PCR developed was used for direct detection of S. agalactiae in milk, using for the first time with gram-positive bacteria the nucleic acid-binding properties of diatomaceous earth. The test, which has high specificity, high sensitivity (100 cfu/mL), and can be carried out in less than 24 h, represents an innovative diagnostic tool for the detection of S. agalactiae in milk.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".