Re-description of <em>Luciobarbus barbulus</em> Heckel 1849 a <em>Cyprinidae</em> species of Persia
Bibliographic record
Abstract
Western Iran barb species are scientifically, environmentally, and economically important. Some of them are the largest riverine freshwater species, which will grow in size and weight to 170 cm, and 120 kg respectively. There is little information on taxonomy or environmental status of these species Luciobarbus barbulus is one of the important large species. During the resent year since 2013, in order to find the new record of large barb species, sampling program carried out in western Iran,. Luciobarbus barbulus briefly described by Heckel (1849) but during the time, have been synonymized with other related species or vice versa, other similar species miss-identically have been known as this species. Also the synonymy of Luciobarbus barbulus with L. pectoralis remains uncertain. The possible syntypes of L. barbulus in Vienna Museum (NMW 53957 and NMW 6596) are in too poor condition to be of any value, being mostly bones, and are dried, and. The fleshy lip of NMW 6596, (measures 119.3 mm standard length) fold of the original description could not be discerned, teeth are missing and the dorsal fin is broken off short. In 1997 this was the only syntype recognized. The catalog in Vienna lists only 1 fish, while Heckel's description refers to several fishes!. So designing of Lecotype and re-description of L. barbulus is essential. In this paper the details of description and differences between these species are given.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.009 |
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".