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Record W2999612125 · doi:10.20302/nc.2019.28.29

New species from the family Hydroptilidae in Croatian fauna collected in the Krka National Park with particular notice to biodiversity and DNA barcoding

2019· article· en· W2999612125 on OpenAlexfundno aff
Mladen Kučinić, Anđela Ćukušić, Antun Delić, Martina Podnar, Danijela Gumhalter, Vlatka Mičetić Stanković, Mladen Plantak, Goran Čeple, Hrvoje Plavec, Drago Marguš

Bibliographic record

VenueNatura Croatica · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
FundersHrvatska Zaklada za ZnanostMcMaster UniversitySveučilište u Zagrebu
KeywordsDNA barcodingFaunaBiologyBiodiversityCaddisflyNational parkEcologyZoologyLarva

Abstract

fetched live from OpenAlex

In this study we present: two species of caddisflies new for Croatian fauna from the family Hydroptilidae (Hydroptila simulans Mosley, Orthotrichia costalis Curtis), first DNA barcoding of caddisfly species in the Krka National Park and a discussion about recorded caddisfly fauna in the Krka NP from this study.From a faunistic point of view several species are interesting: Hydropsysche mostarensis Klapálek, Hydroptila simulans Mosely, Hydroptila forfcipata Eaton, Orthotrichia costalis Curtis and Tinodes pallidulus McLachlan.For the species Oecetis notata Rambur we have recorded interesting taxonomical remarks.Furthermore, within this study we used DNA barcoding which showed to be a very good and useful method for identification of very small and morphologically similar species from the family Hydroptilidae, or females from the family Psychomyiidae.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.214
Teacher spread0.197 · 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".

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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