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Record W2097657579 · doi:10.1006/jmsc.2002.1248

In situ target strength studies on Atlantic redfish (Sebastes spp.)

2002· article· en· W2097657579 on OpenAlexafffundabout
Stéphane Gauthier

Bibliographic record

VenueICES Journal of Marine Science · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsTarget strengthSebastesShoalFisheryFish <Actinopterygii>In situRange (aeronautics)OceanographyGeologyEnvironmental scienceVolume (thermodynamics)CalibrationBiologyMathematicsStatisticsMaterials scienceGeographyPhysicsMeteorology

Abstract

fetched live from OpenAlex

In situ acoustic target strength (TS) experiments were conducted on Atlantic redfish ( Sebastes spp.) in Newfoundland waters (1996–1998) using deep-tow dual beam and hull-mounted split beam echosounders (38 kHz). The dual and split beam mean TSs did not differ. The deep-tow system was deployed at various depths over several aggregations. Calibration corrections were made for depths from 5–70 m (<1 dB). The TS declined at ranges <50 m from the top of the fish shoal suggesting avoidance behaviour. It was biased upward at ranges >200 m and a number of fish per sampled volume >0.04. After being controlled for variations related to range, reverberation volume and fish density the TS did not differ with respect to depth, distance from bottom, fish sex ratio, condition factor or weight. The mean length was the dominant influence on the mean TS. Pooled ex situ experimental data and controlled in situ data – which did not differ – indicated a length-based regression (weighted by s.e. −1 ) in standard format: TS=20 log [length (cm)] −68.7 (r 2 =0.49).

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)0.001
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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.017
GPT teacher head0.249
Teacher spread0.233 · 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

Citations29
Published2002
Admission routes3
Has abstractyes

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