MORPHOLOGICAL AND ECOLOGICAL VARIATION WITHIN THE<i>ACHNANTHIDIUM MINUTISSIMUM</i>(BACILLARIOPHYCEAE) SPECIES COMPLEX<sup>1</sup>
Bibliographic record
Abstract
Variation of frustular morphology within the Achnanthidium minutissimum (Kütz.) Czarn. species complex was studied in type populations of 12 described taxa and in 30 recent North American river samples. The SEM observations in this study and other publications showed that ultrastructural characters on their own do not discriminate among taxa within the A. minutissimum complex. Therefore, an attempt was made to use other characters, such as valve shape and striation pattern, to delineate morphological groups. The sliding‐landmarks method was used to obtain valve‐shape descriptors. These shape variables were combined with conventional morphological characters in multivariate analyses. It was shown that some historically recognized taxa are morphologically distinct, while others are difficult to differentiate. Morphological grouping of “old” taxa most similar to A. minutissimum did not correspond to their taxonomic hierarchy in contemporary diatom floras. Morphometric analysis of a data set of 728 specimens from North American rivers revealed six morphological groups, although it was impossible to draw clear boundaries among them. These morphological groups differed significantly in their ecological characteristics and could be recommended as indicators of water quality. Application of the discriminant function analysis based on shape variables and striation pattern showed that North American specimens could be more consistently classified into the six groups identified in our analysis than into historically recognized taxa.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".