Toxicity, morphology and distribution of <i>Pseudo-nitzschia calliantha</i>, <i>P. multistriata</i> and <i>P. multiseries</i> (Bacillariophyta) from the northwestern Sea of Japan
Bibliographic record
Abstract
Abstract Toxicity, morphology and distribution patterns of three bloom-forming species of the diatom genus Pseudo-nitzschia (potential producers of the neurotoxin domoic acid and causative organisms of amnesic shellfish poisoning) from Peter the Great Bay in the northwestern Sea of Japan are presented. Pseudo-nitzschia calliantha, P. multistriata and P. multiseries bloomed in Peter the Great Bay in the fall, with abundances exceeding 106 cells l-1. This is the first report of toxicity in P. multiseries from Russian waters. Domoic acid was found in stationary-phase (days 20–35) cultures of P. multiseries isolated from Peter the Great Bay at concentrations varying between 180 and 5390 ng ml-1 or 2 to 21 pg cell-1, which is in the range reported for other isolates of P. multiseries. The Russian isolate had an increasing ability to produce domoic acid over time in culture rather than the usual trend of decreasing toxicity. No domoic acid was detected (<2 ng ml-1) in cultures of P. calliantha and P. multistriata from the same locality. The Russian isolate of P. multiseries produced gametes when mated with the Canadian strains of the opposite mating type, but they never developed into zygotes, auxospores or large initial cells. This suggests that there might be “cryptic” species within P. multiseries. However, a comparison of molecular and morphometric data between the Russian and Canadian strains showed that they indeed belong to the same species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".