Potential application of low-stringency single specific primer-PCR in the identification of<i>Leptospira</i>in the serum of patients with suspected leptospirosis
Bibliographic record
Abstract
In this study we tested the potential use of low-stringency single specific primer-PCR (LSSP-PCR) for genetically typing Leptospira directly from biological samples. Serum samples obtained from 29 patients with clinically suspected leptospirosis were amplified by specific PCR, using the previously selected G1 and G2 primers. The PCR products of approximately 300 bp were subsequently used as a template for LSSP-PCR analysis. We were able to produce genetic signatures from the leptospires present in the human samples, which permitted us to make a preliminary identification of the infective serovar by comparing the LSSP-PCR profiles obtained directly from serum samples with those from reference leptospires. Thus, LSSP-PCR has the potential to become a useful diagnostic tool for identifying leptospires in biological samples without the need for bacteria isolation and culture.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".