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Record W2205142828

A New Record of Paracobitis rhadinaea (Regan, 1906)

2013· article· en· W2205142828 on OpenAlexaboutno aff
A. Rahdari

Bibliographic record

VenueCaspian journal of environmental sciences · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFish Biology and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCobitidaeGeographyCypriniformesFisheryFishingWetlandArchaeologyFish <Actinopterygii>BiologyEcology
DOInot available

Abstract

fetched live from OpenAlex

After around a hundred years of being without any record of occurrence of Paracobitis rhadinaea, a species of Nemacheiline loach, in Sistan basin, southeast of Iran, the year 2012 was the turning point of wild life in this area. Twenty-five specimens were caught from Chahnimeh Reservoir, a water body adjacent to the Hamoun Wetland in Sistan basin. Morphometric and meristic characteristics were measured. REFERENCES  Annandale, N. and Hora, S. L (1920) The fish of Sistan. Records of the Indian Museum, 18:151-203, pls. XV-XVII (includes: - Appendix. Note on the fisheries of the delta of the Helmand and on the use of shaped rafts of bulrushes in India and Seistan, by N. Annandale). Banarescu, P. M. and Nalbant, T. T (1995) A generical classification of Nemacheilinae with description of two new genera (Teleostei: Cypriniformes: Cobitidae). Travaux du Museum d'Histoire Naturelle Grigore Antipa, Bucuresti, 35:429-496.  Banarescu, P., Nalbant T.T. and Chelmu, S (1972) Revision and geographical variation of Sabanejewia aurata in Romania and the origin of S. bulgarica and S. romanica (Pisces, Cobitidae). Annotationes Zoologicae et Botanicae Bratislava, 75: 49.  Boudaghpour, S (2011) Arid Season Affecting Hamun Lake in South East Iran Water, Fishing and Agriculture Crisis. International Conference on Food Engineering and Biotechnology. IACSIT Press, Singapoore. Coad B.W (1980) Environmental change and its impact on the freshwater fishes of Iran. Biological Conservation, 19 (1): 51– 80.   Coad, B.W (1981) Fishes of Afghanistan, an annotated check-list. Publication Zoology Natural Museum Canadian. 14:23p.  Coad, B. W (2012) Freshwater Fishes of Iran. http://www.briancoad.com. Chaudhuri, B. L (1909) Descriptions of new species of Botia and Nemachilus. Records of the Indian Museum, 3:339-342.  Erk'akan, F., S.C. Ozeren and Nalbant, T.T (2008) Cobitis evreni sp. Nova-A New Spined loach Species (Cobitidae) from the Southern Turkey. Journal of Fisheries International, 3(4): 112-114.  Eschmeyer, W.N (2004) Catalog of fishes. Updated database version of January 2004. Catalog databases as made available to FishBase in January 2004.   Fowler, H. W. and Steinitz, H(1956) Fishes from Cyprus, Iran, Iraq, Israel and Oman. Bulletin of the Research Council of Israel, 5B:260-292.  Kottelat, M. and Freyhof, J (2007) Handbook of European Freshwater Fishes. Kottelat, Cornol, Switzerland and Freyhof, Berlin, Germany, 646 p.  Mansoori, J (1994) The Hamoun Wildlife Refuge. Heidelberg: Max Kasparek Verlag: 1-57.  Mousavi-Sabet, H., Gharaei, A. and Ghaffari, M (2013) Threatened fishes of the world: Paracobitis rhadinaeus (Regan, 1906) (Nemacheilidae). Croatian Journal of Fisheries, 71: 87-89.  Nalbant, T.T. and Bianco, P.G (1998) The loaches of Iran and adjacent regions with description of six new species (Cobitoidea). Italian Journal of Zoology, 65:109-125. Nelson, J.S (2006) Fishes of the world. 4th ed. John Wiley & Sons, Inc., 141:622 p.  Nikol'skii, G. V (1947) Gol'tsy besstochnykh vodoemov Turkmenii [The loaches of the inland waters of Turkmenia]. Byulleten' Moskovskogo Obshchestva Ispytatelei Prirody, Otdel Biologii, 52:29-34.  Whitney, J.W (2006) Geology, water, and wind in the lower Helmand Basin, southern Afghanistan: U.S. Geological Survey Scientific Investigations Report 2006–5182, 40 p.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.013
GPT teacher head0.185
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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