Temporal and Spatial Variation in the Abundance of Total and Pathogenic Vibrio parahaemolyticus in Shellfish in China
Bibliographic record
Abstract
We investigated the abundance of total and pathogenic Vibrio parahaemolyticus in shellfish sampled from four provinces in China during May 2013 and March 2014 using the most probable number-polymerase chain reaction (MPN-PCR) method. Total V. parahaemolyticus was detected in 67.7% of 496 samples. A total of 38.1% and 10.1% of samples exceeded 1,000 MPN g(-1) and 10,000 MPN g(-1), respectively. V. parahaemolyticus densities followed a seasonal and geographical trend, with Guangxi and Sichuan shellfish possessing total V. parahaemolyticus levels that were 100-fold higher than those of the Liaoning and Shandong regions. Moreover, the levels of V. parahaemolyticus were at least 10-fold higher in the summer and autumn than in the cooler seasons. Pathogenic V. parahaemolyticus levels were generally lower than total V. parahaemolyticus levels by several log units and tended to be high in samples contaminated with high total V. parahaemolyticus levels. The aqua farms had a lower prevalence but higher abundance of total V. parahaemolyticus compared to retail markets. The catering markets showed the lowest levels of total V. parahaemolyticus, but 20.0% of samples exceeded 1,000 MPN g(-1). The levels of both total and pathogenic V. parahaemolyticus in oysters were higher than in clams. The log-transformed abundance of V. parahaemolyticus was significantly correlated with both water temperature and air temperature but not water salinity. These results provide baseline contamination data of V. parahaemolyticus in shellfish in China, which can be applied to local risk assessments to prioritize risk control to key sectors and evaluate the effectiveness of future control measures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".