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Record W4379052027 · doi:10.1051/e3sconf/202339007014

Historical changes of biodiversity in Baikal Siberia and dynamics of nest settlements of the Great Cormorant (Phalacrocorax carbo L., 1758) in the first quarter of the XXI century

2023· article· en· W4379052027 on OpenAlexaboutno aff
E. N. Yelayev, Tsidip Z. Dorzhiev, Aleksandr Ananin, Sergey V. Pyzh’yanov, Irina A. Ayurzanaeva

Bibliographic record

VenueE3S Web of Conferences · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsCormorantBayGeographyFaunaEcologyPopulationBiodiversityNest (protein structural motif)Human settlementQuarter (Canadian coin)FisheryArchaeologyBiologyPredationDemography

Abstract

fetched live from OpenAlex

The article presents the history of nesting, disappearance from the fauna and the current spatial distribution of Great Cormorant (Phalacrocorax carbo L., 1758) breeding colonies in Baikal Siberia. The main research sites were the Selenga River Delta, Strait of the Maloye More and islands of the Chivyrkuy Bay, Upper Angara Bay on Baikal Lake; the Upper Angara and Barguzin hollows, Gusinoe Lake in the Pribaikalye and Transbaikalye, where this species once lived according to well-known literary sources in the XVII to the middle of the XX centuries. Direct accounting of newly nesting birds after a 50-year absence in known colonies with young birds that flew out by autumn, as well a non-breeding birds, allowed us to estimate the total number of cormorants in 2021 on Baikal Lake. It amounted to 39-40 thousand birds, which indicates the settlement of the species in the Baikal Lake ecosystem and population stabilization in accordance with the environmental ecological capacity.

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 score0.079
Threshold uncertainty score0.157

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 communication0.0000.000
Open science0.0000.001
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 head0.025
GPT teacher head0.193
Teacher spread0.168 · 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
Published2023
Admission routes1
Has abstractyes

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