Phylogenetic status of brown trout<i>Salmo trutta</i>populations in five rivers from the southern Caspian Sea and two inland lake basins, Iran: a morphogenetic approach
Bibliographic record
Abstract
Interrelationships, origin and phylogenetic affinities of brown trout Salmo trutta populations from the southern Caspian Sea basin, Orumieh and Namak Lake basins in Iran were analysed from complete mtDNA control region sequences, 12 microsatellite loci and morphological characters. Among 129 specimens from six populations, seven haplotypes were observed. Based on mtDNA haplotype data, the Orumieh and southern Caspian populations did not differ significantly, but the Namak basin-Karaj population presented a unique haplotype closely related to the haplotypes of the other populations (0·1% Kimura two-parameter, K2P divergence). All Iranian haplotypes clustered as a distinct group within the Danube phylogenetic grouping, with an average K2P distance of 0·41% relative to other Danubian haplotypes. The Karaj haplotype in the Namak basin was related to a haplotype (Da26) formerly identified in the Tigris basin in Turkey, to a Salmo trutta oxianus haplotype from the Aral Sea basin, and to haplotype Da1a with two mutational steps, as well as to other Iranian haplotypes with one to two mutational steps, which may indicate a centre of origin in the Caspian basin. In contrast to results of the mtDNA analysis, more pronounced differentiation was observed among the populations studied in the morphological and microsatellite DNA data, except for the two populations from the Orumieh basin, which were similar, possibly due to anthropogenic causes.
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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".