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Macrozoobenthos of the Olyutorsky Bay (Bering Sea) a quarter of century later: composition, distribution, communities

2022· article· en· W4223564662 on OpenAlexaboutno aff
V. А. NADTOCHY, Nikolai V. Kolpakov

Bibliographic record

VenueIzvestiya TINRO · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
Fundersnot available
KeywordsBayBiomass (ecology)OceanographyAbundance (ecology)Quarter (Canadian coin)Range (aeronautics)FisheryEnvironmental scienceGeographyBiologyGeologyArchaeology

Abstract

fetched live from OpenAlex

Results of two bottom grab surveys in the Olyutorsky Bay of the Bering Sea conducted in 1985 (37 stations with 60 samples in the depth range of 20–200 m) and 2012 (26 stations with 48 samples at the depths of 51–270 m) are compared. Average biomass of macrozoobenthos was rather stable: 561.1 ± 95.2 g/m2 in 1985 and 581.3 ± 94.5 g/m2 in 2012. Sea urchins, bivalves and polychaetes dominated by biomass in 1985 (84.7 % of the total biomass for these 3 groups), but sipunculids appeared in the list of the dominant taxonomic groups in 2012 when 91.3 % of the total biomass consisted of the top 4 groups. The main communities of macrozoobenthos practically retained their location and quantitative parameters. There is concluded that composition, distribution and abundance of macrozoobenthos in the Olyutorsky Bay were stable over a quarter of century.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.199
Teacher spread0.183 · 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.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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