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Паразиты рыб горных озер бассейна Верхней Колымы. 1. Озера большой и малый Дарпир.

2021· article· en· W4200521590 on OpenAlexfundno aff
В. В. Поспехов, Г. И. Атрашкевич, O. M. Orlovskaya, Е. И. Михайлова

Bibliographic record

VenueBulletin of the North-East Science Center · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
FundersUniversity of Manitoba
KeywordsBiologySuckerFaunaSculpinHelminthsDiversity of fishZoologyMinnowCypriniformesEcologyCestodaFisheryCyprinidaeFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The first data on the parasite fauna of fish from the mountain lakes Bolshoy and Maly Darpir at the southern spurs of the Chersky Ridge (Momsky District, Yakutia) are presented. 7 species of fish have been studied, in which 34 species of parasites have been found: 33 species of helminths and 1 species of parasitic copepods, belonging to 22 genera, 16 families, 12 orders, 7 classes of 4 types of the animal kingdom. Trematodes completely dominate by the number of species among helminths (16 species); cestodes are half as many (8 species); these are followed by nematodes and spiny-headed worms (5 and 4 species, respectively). The greatest variety of parasites was found in the East Siberian grayling (22 species) and the Arctic char (19 species). Next to the latter in terms of the number of parasite species, there went the Kolyma sculpin (13 species), round whitefish (10 species each), sucker (9 species), eelpout, and common minnow (7 species each). Only one parasite species, the Neoechinorhynchus salmonis Ching, 1984 spiny-headed worm, is common for all studied fish. The second species of spiny-headed worms, Pseudoechinorhynchus borealis (Linstow, 1901), not found only in the round whitefish, was first recorded in fish of the Okhotsk-Kolyma area and in the sucker as a new definitive host.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.004

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 head0.011
GPT teacher head0.265
Teacher spread0.254 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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