The diversity of diatom genera: relationship to genetic variability within the genus Frustulia and the role of geography
Bibliographic record
Abstract
The occurrence of some diatoms depends on degree of pollution and water quality. Due to this attribute are diatoms used as indicators for the environmental bioassessment. But the maximum use of diatoms for this purpose is complicated by high number of species which are defined based on the ultrastructural morphological features which are indistinguishable without the electron microscope. The aims of this study were to find out the influence of environmental factors, types of habitat and geography on the structure of diatom community. And find out if richness of higher taxonomic levels is correlated with species richness, in this case if it responds with the genetic diversity within diatom species complex Frustulia crassinervia-saxonica. In this study, 49 permanent slides from natural samples were analyzed. Samples were taken from benthos of different types of freshwater habitat - lakes, dams, pools, peat bogs, stream, wet wall on diverse localities in Europe, Canada, Greenland, Chile and New Zealand. In all slides were counted 300 cells which were determined based on the morphological features on genera level. Altogether 43 benthic genera were identified. The results of this thesis showed that number of genera correlated with pH gradient but do not correlate with other environmental factors -...
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".