DNA barcoding and molecular biodiversity inventory of the ichthyofauna of the Czech Republic
Bibliographic record
Abstract
The Czech Republic lies in the centre of Europe and from the point of view of hydrology its territory belongs to three drainage areas – those of the North Sea, Black Sea and Baltic Sea. This fact has an important influence on abundant species diversity of its ichthyofauna. The occurrence of 94 species of lampreys and fish of 13 orders and 23 families was historically confirmed here both in natural waters and fish cultures. Some of them are already extinct. Another 24 species face various levels of endangerment. The Czech-Canadian project within the iBOL initiative analyzed about 1,500 individuals from about 200 locations. Using a comprehensive approach (morphology, DNA barcoding, nDNA analysis) the haplotype variability was identified and pure species from hybrids were differentiated. At least in 5 genera, higher species variability than that described in literature was identified. DNA barcodes for about 72 recent indigenous and non-indigenous species were prepared. A new reference collection of all fish species of the Czech Republic for the National Museum was assembled. Efficiency of a new identification method, S7indel diagnostics, for taxonomic and biodiversity purposes was evaluated.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".