Numerical analysis of small Arctic diatoms (Bacillariophyceae) representing the <i>Staurosira</i> and <i>Staurosirella</i> species complexes
Bibliographic record
Abstract
T.M. Paull, P.B. Hamilton, K. Gajewski and M. LeBlanc. 2008. Numerical analysis of small Arctic diatoms (Bacillariophyceae) representing the Staurosira and Staurosirella species complexes. Phycologia 47: 213–224. DOI:10.2216/07-17.1Small benthic fragilarioid diatoms (Bacillariophyceae) are dominant taxa in circumpolar Arctic lakes and ponds. These small forms are difficult to identify under light microscope (LM) because of valve size, the limited number of visible characters, and considerable morphological variability within populations. For this reason, ultrastructural characters visible only under a scanning electron microscope (SEM) such as areolae and spine structure are usually recommended for species- and even genus-level identification. This is, however, often impractical. In this study we show that selected characters of Staurosirella pinnata (Ehrenberg) Williams & Round and Staurosira venter (Ehrenberg) Cleve & Möller measurable under LM correlate with diagnostic characters that can only be evaluated under SEM. We measured 32 morphological characters from SEM observations of 510 valves representing Staurosirella pinnata sensu Hustedt, Staurosira venter sensu Hustedt, and two morphologically distinct forms of S. venter sensu lato from lakes in Canada, Fennoscandia, and Siberia. Specimens from the circumpolar Arctic region identified as Staurosirella pinnata can be distinguished from Staurosira venter sensu lato using valve width and areola length (at margin), both visible under LM. Specimens with areolae lengths (at margin) larger than 0.4 µm are Staurosirella pinnata. For specimens with areolae lengths (at margin) smaller than 0.4 µm, those with valves wider than 2.9 µm are Staurosira venter sensu lato, whereas those with valves smaller than 2.9 µm are Staurosirella pinnata. Application of these numerical criteria allows for correct identification of 94% of specimens to either Staurosira venter (including morphotypes) or Staurosirella pinnata.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".