INTER‐ AND INTRASPECIFIC COMMUNITY STRUCTURE WITHIN THE DIATOM GENUS <i>PSEUDO‐NITZSCHIA</i> (BACILLARIOPHYCEAE)<sup>1</sup>
Bibliographic record
Abstract
Pseudo‐nitzschia‐ specific PCR primers (PnAll F/R) were designed to amplify a polymorphic region of the internal transcribed spacer 1 (ITS1) from at least 11 Pseudo‐nitzschia species. The primers were used to generate environmental clone libraries from Puget Sound, Washington, and Vancouver Island, British Columbia, to confirm that the primers were specific for Pseudo‐nitzschia and to determine the extent of ITS1 sequence diversity within individual species. All environmental ITS1 sequences generated with PnAll primers displayed the greatest similarity to known Pseudo‐nitzschia ITS1 sequences. The length of cloned ITS1 fragments differed among species but was conserved within a species. Intraspecific genotypes exhibited <3% sequence divergence for seven of the 10 species detected in clone libraries. Several ITS1 genotypes unique to the Pacific Northwest were identified in environmental samples, and other genotypes were more broadly distributed. The Pseudo‐nitzschia primers were also used to develop an automated ribosomal intergenic spacer analysis (ARISA) to rapidly identify Pseudo‐nitzschia species in environmental samples based on species‐specific variation in the length of the targeted ITS1 region. The ARISA peaks were then associated with the environmental clone sequences for Pseudo‐nitzschia species. Surveying the genetic composition of communities at both the inter‐ and intraspecific levels will enhance our understanding of Pseudo‐nitzschia bloom dynamics.
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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) | 0.001 | 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".