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Record W1988252275 · doi:10.2960/j.v27.a10

Density Dependant Sex Change in Northern Shrimp, <i>Pandalus borealis</i>, on the Scotian Shelf

2000· article· en· W1988252275 on OpenAlexaff
Peter Koeller, Robert Mohn, M. Etter

Bibliographic record

VenueJournal of Northwest Atlantic Fishery Science · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
Fundersnot available
KeywordsShrimpSex ratioFisheryStock (firearms)BiologyAbundance (ecology)Population densityDensity dependencePopulationDemographyGeography

Abstract

fetched live from OpenAlex

We investigated factors affecting sex change in the Pandalid shrimp Pandalus borealis on the Scotian Shelf. Transition from male to female occurred at different sizes and ages, and could not be related to a minimum size or age. Our data did not show a positive relationship between abundance of older females and shrimp size at sex transition, nor a negative relationship between male:female sex ratio and shrimp size at transition, that would be expected if the population was compensating for decreases in reproductive capacity as predicted by sex allocation theory. Size at transition was inversely related to female density, which was attributable to density dependent growth affecting all stages. Density dependant growth also appeared to explain previously reported results which had been used to support sex allocation theory. Density was the most important factor determining individual growth at high densities while at low densities other factors, including temperature, were also an important determinant of growth. We conclude that a decrease in the size at transition can be indicative of a healthy, as well as a declining stock, and must be fully understood before it can be used as an indicator of stock status. Possible alternative mechanisms for regulating sex change in Pandalids 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 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)0.002
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 score0.101
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.240
Teacher spread0.223 · 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

Citations30
Published2000
Admission routes1
Has abstractyes

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