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Record W3005347119 · doi:10.1051/kmae/2020003

Mass appearance of the Ponto-Caspian invader<i>Pontogammarus robustoides</i>in the River Tisza catchment: bypass in the southern invasion corridor?

2020· article· en· W3005347119 on OpenAlexaff
Zoltán Csabai, Péter Borza, Tomasz Rewicz, Bálint Pernecker, Balázs Berta, Arnold Móra

Bibliographic record

VenueKnowledge and Management of Aquatic Ecosystems · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsUniversity of Guelph
FundersNarodowa Agencja Wymiany AkademickiejDebreceni EgyetemPécsi TudományegyetemEmberi Eroforrások Minisztériuma
KeywordsBiological dispersalTributaryGeographyPopulationDrainage basinElectrofishingFisheryChannel (broadcasting)EcologyHabitatBiologyCartography

Abstract

fetched live from OpenAlex

The river Danube is the backbone of the ‘southern invasion corridor’, one of the most important passages for the spread of Ponto-Caspian invaders in Europe. However, not all of these species used the passive or active upstream movement in the main channel to reach the upper sections and tributaries, some found detours. Mass occurrences of the Ponto-Caspian peracarid, Pontogammarus robustoides (Sars, 1894) were recorded at 17 sites along the entire Hungarian section of the River Maros, for the first time in the River Tisza catchment and also in Hungary. Those populations are found ca. 707 km upstream from the closest known and confirmed locality in the lower Danube section. We confirmed their identity by DNA barcoding and showed that all individuals fit in with the lower Danube population, thus identifying the source of this introduction. The most likely vector allowing the jump dispersal of the species is fish stocking in the Romanian section of the River Maros, which − combined with downstream drift to the Serbian Danube section and the relatively busy ship traffic between Belgrade and Vienna − might provide the opportunity to bypass the dispersal barrier represented by the unregulated Middle Danube and open the way towards Western Europe.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.216
Teacher spread0.195 · 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 teacher head, 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".

Quick stats

Citations14
Published2020
Admission routes1
Has abstractyes

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