IDENTIFICATION AND ASSESSMENT OF DOMOIC ACID PRODUCTION IN OCEANIC <i>PSEUDO‐NITZSCHIA</i> (BACILLARIOPHYCEAE) FROM IRON‐LIMITED WATERS IN THE NORTHEAST SUBARCTIC PACIFIC<sup>1</sup>
Bibliographic record
Abstract
We identified and investigated the potential toxicity of oceanic Pseudo-nitzschia species from Ocean Station Papa (OSP), located in a high-nitrate, low-chlorophyll (HNLC) region of the northeast (NE) subarctic Pacific Ocean. Despite their relatively low abundances in the indigenous phytoplankton assemblage, Pseudo-nitzschia species richness is high. The morphometric characteristics of five oceanic Pseudo-nitzschia isolates from at least four species are described using SEM and TEM. The species identified are Pseudo-nitzschia dolorosa Lundholm et Moestrup, P. granii Hasle, P. heimii Manguin, and P. cf. turgidula (Hust.) Hasle. Additional support for the taxonomic classifications based on frustule morphology is provided through the sequencing of the internal transcribed spacer 1 (ITS1) rDNA. Pseudo-nitzschia species identification was also assessed by the construction of ITS1 clone libraries and using automated ribosomal intergenic spacer analysis (ARISA) for environmental samples collected during the Subarctic Ecosystem Response to Iron Enrichment Study (SERIES), conducted in close proximity to OSP in July of 2002. Based on ITS1 sequences, the presence of P. granii, P. heimii, P. cf. turgidula, and at least five other putative, unidentified Pseudo-nitzschia ITS1 variants was confirmed within iron-enriched phytoplankton assemblages at OSP. None of the oceanic isolates produced detectable levels of particulate domoic acid (DA) when in prolonged stationary phase due to silicic acid starvation. The lack of detectable concentrations of DA suggests that either these strains produce very little or no toxin, or that the physiological conditions required to promote particulate DA production were not met and thus differ from their coastal, toxigenic congeners.
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 | 0.001 | 0.001 |
| 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".