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Record W2065620707 · doi:10.1017/s0025315408001628

Predation by the sea urchin <i>Strongylocentrotus droebachiensis</i> on capsular egg masses of the whelk <i>Buccinum undatum</i>

2008· article· en· W2065620707 on OpenAlexaff
Clément Dumont, Jean‐Sébastien Roy, John H. Himmelman

Bibliographic record

VenueJournal of the Marine Biological Association of the United Kingdom · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsWhelkStrongylocentrotus droebachiensisSea urchinPredationFisheryBiologyCapsuleZoologyEcologyBotany

Abstract

fetched live from OpenAlex

We evaluated sea urchin Strongylocentrotus droebachiensis predation on egg masses of the whelk Buccinum undatum . The urchin actively grazes on the egg masses, even as they are being deposited on the bottom. Whelks preferentially lay their egg masses on vertical areas where urchin densities are 4-fold less than on flat areas. This strategy is advantageous, as experimental trials showed that the loss in the mass of capsules was 4 fewer on walls than on flat areas. Nevertheless, a high proportion of egg masses on walls show damage from predation. Urchins provided with egg masses in the laboratory, ingested the capsules at a steady rate over a 9-d period (5 urchins ingested 2.8 g.d-1). Urchins provided agar discs that included a preferred alga and whelk capsule walls ingested the discs at a rate that was half that observed for discs that only included the alga. Discs that included the preferred alga and capsule contents were eaten at the same rate as discs that only included the alga. Thus, capsule walls, but not the capsule contents, provide a defence against urchin predation. Laying aggregate egg masses likely provides only a limited advantage, as the attachment surface does not increase with the number of egg masses deposited together, so the risk of detachment increases. Consideration of the interactions between urchins and whelks is important in managing the fisheries of the two species.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.066
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.200
Teacher spread0.180 · 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.

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

Citations15
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Marine Biological Association of the United KingdomSame topicMarine and coastal plant biologyFrench-language works237,207