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Record W2117915978 · doi:10.1139/f10-042

Abundance and distribution of Antarctic krill (Euphausia superba) nearshore of Cape Shirreff, Livingston Island, Antarctica, during six austral summers between 2000 and 2007

2010· article· en· W2117915978 on OpenAlexvenueno aff
Joseph D. Warren, David A. Demer

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorNational Science Foundation
KeywordsEuphausiaKrillAntarctic krillOceanographyEcho soundingBiomass (ecology)Environmental scienceFisheryGeologyBiology

Abstract

fetched live from OpenAlex

Abundance and distribution of Antarctic krill ( Euphausia superba ) in the nearshore waters north of Livingston Island, Antarctica, were characterized from six small-boat surveys conducted in late January or early February from 2000 to 2007. The first three surveys (2000, 2002, 2004) were conducted using a 120 kHz split-beam echosounder to measure water column acoustic backscatter. The last three surveys (2005–2007) were conducted using 38 kHz and 200 kHz single-beam echosounders. A portion of the acoustic backscatter was attributed to Antarctic krill based on the results of net tows, underwater video observations, and a multiple-frequency acoustic classification algorithm. The annual mean krill biomass density in the survey area ranged from 11 to 84 g·m–2. Results are compared with the western Scotia Sea area of the US Antarctic Marine Living Resources (AMLR) program’s acoustic surveys of krill biomass density for the same years. Nearshore krill biomass densities were significantly larger (t test, p < 0.05), more stable, and the coefficients of variation were smaller than the much larger AMLR surveys. Increased competition between seals, penguins, and humans for the nearshore krill resource, especially during the austral summer months, could impact the recruitment success of these land-based krill predators. Implications of nearshore krill biomass on small-scale management units are discussed.

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 score0.127
Threshold uncertainty score0.253

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 studies0.0010.000
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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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

Citations26
Published2010
Admission routes1
Has abstractyes

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