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Record W2159665703 · doi:10.1093/icesjms/fsp097

Passive- and active-acoustic properties of a spawning Atlantic cod (Gadus morhua) aggregation

2009· article· en· W2159665703 on OpenAlexafffundabout
Susan B. Fudge, George A. Rose

Bibliographic record

VenueICES Journal of Marine Science · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGadusDiel vertical migrationAtlantic codOceanographyFisheryBaySeabedEcho soundingEnvironmental scienceGeologyMarine mammals and sonarFish <Actinopterygii>BiologySonar

Abstract

fetched live from OpenAlex

Abstract Fudge, S. B., and Rose, G. A. 2009. Passive- and active-acoustic properties of a spawning Atlantic cod (Gadus morhua) aggregation. – ICES Journal of Marine Science, 66: 1259–1263. A spawning aggregation of Atlantic cod (Gadus morhua) was observed at depths of 40–50 m with passive- and active-acoustic sensors at the Bar Haven grounds in Placentia Bay, Newfoundland, in April 2003. A hydrophone was positioned on the seabed beneath the aggregation, while a 38-kHz split-beam echosounder was moored at the sea surface above it for 18.5 h. Ten grunts were recorded with peak frequencies ranging from 30 to 250 Hz and durations of nearly 300 ms. These grunts are similar to the sounds recorded in the presence of captive, spawning cod from the same substock. The echogram reveals that cod exhibit diel, vertical-migratory behaviour, densely aggregating near the seabed by day and forming columns that extend approximately halfway to the surface at night. This is the first study to demonstrate that cod produce sounds and form columns while migrating vertically during night-time spawning.

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 score0.012
Threshold uncertainty score0.024

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 studies0.0000.000
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 head0.017
GPT teacher head0.235
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

Citations36
Published2009
Admission routes3
Has abstractyes

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