Bacterial dynamics in ballast water during trans-oceanic voyages of bulk carriers: environmental controls
Bibliographic record
Abstract
Bacterial abundance, population dynamics, and related environmental parameters were determined in ballast water during 2 trans-Pacific voyages from Japan to the west coast of Canada and 2 trans-Atlantic voyages from the Netherlands to the east coast of Canada.Water samples were collected from ballast tanks that either underwent mid-ocean exchange (MOE) or were unexchanged (control).Bacterial abundances in the MOE and control tanks were not significantly different at the end of the voyage.Moreover, abundances were not lower immediately after compared with immediately before MOE, suggesting that MOE alone is not effective in reducing ballast water bacterial abundances.Results of this study suggest that the duration of the voyage plays a critical role in determining the potential bacterial propagule pressure.Although the bacterial growth dynamics were complex, we found robust relationships and a highly significant predictive relationship between bacterial abundance and both temperature and dissolved oxygen concentrations of the ballast water (p < 0.001).This robust relationship allows the prediction of potential bacterial propagule pressure from environmental characteristics within the ballast tanks.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".