Variability of Pseudo-<i>nitzschia</i> and domoic acid in the Juan de Fuca eddy region and its adjacent shelves
Bibliographic record
Abstract
The Juan de Fuca eddy is a toxic “hot spot.” Domoic acid (DA) was detected in the eddy during each of six cruises over a 4-yr study, although Pseudo-nitzschia abundance and toxin concentrations were highly variable. During the September 2004 eddy bloom, Pseudo-nitzschia spp. exceeded 13 × 106 cells L−1, and particulate DA reached 80 nmol L−1. Of the >10 species of Pseudo-nitzschia identified in this region, those coincident with the most toxic blooms are P. cf. pseudodelicatissima, P. cuspidata, P. multiseries, and P. australis. However, the presence of any particular species could not be used as an indicator of toxicity because of the high level of variability in intracellular DA in field assemblages. Pseudo-nitzschia cells were typically associated with blooms of other diatom taxa but also were coincident with blooms of euglenoids and dinoflagellates in the eddy region. Pseudo-nitzschia always comprised <17% of the total carbon biomass, thereby rendering remote sensing an unsuitable means for predicting toxigenic Pseudo-nitzschia blooms in this region. Our results support the hypothesis that the Juan de Fuca eddy region and not the nearshore zone is the primary initiation site for toxic blooms of Pseudo-nitzschia affecting the Washington coast. Although particulate DA was observed near the edges of the Columbia River plume, whether toxin can be produced in situ in plume water is not resolved. No first-order predictive relationships were found for either Pseudo-nitzschia abundance or DA concentration and environmental data from all six cruises.
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 | 0.000 | 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 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".