MétaCan
Menu
← Back to cohort
Record W6912548152 · doi:10.5281/zenodo.5987557

Apatura metis Freyer 1829

2018· article· en· W6912548152 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsMetisMontenegroPopulationRange (aeronautics)Period (music)Shore

Abstract

fetched live from OpenAlex

Apatura metis Freyer, 1829 —This species was only mentioned by Jakšić (1988) and Švara et al. (2015) from Skadar Lake. It is widespread along much of the northern side of the lake where its host plant Salix alba L.grows in abundance (Franeta pers. obs.). Compared to its European distribution (Masui et al. 2011), the Skadar Lake population is very isolated, almost 300km from the nearest Greek populations and about the same distance from the closest Serbian colonies (Pamperis 2009; Miljević & Popović 2014), and for some time there was doubt regarding its occurrence in this region. The species has recently been observed on the Albanian shores of the Skadar Lake (Micevski et al. 2015). The presence of A. metis in Montenegro might be overlooked by its unusual phenology, compared to other populations from the rest of its European range (Masui et al. 2011). It usually starts to fly at the end of June and continues until the second half of July, with a peak flight period in the first week of July (Franeta pers. obs.). The number of generations at the Skadar Lake colony is yet to be determined and it is quite possible that another (2nd) generation might occur later in the season.

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 score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.004

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 head0.018
GPT teacher head0.221
Teacher spread0.203 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicAquatic Ecosystems and Phytoplankton Dynamics→French-language works237,207→