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Record W2133488901 · doi:10.4319/lo.2006.51.3.1485

Spawning events in small and large populations of the green sea urchin <i>Strongylocentrotus droebachiensis</i> as recorded using fertilization assays

2006· article· en· W2133488901 on OpenAlexaff
Julien Gaudette, Richard A. Wahle, John H. Himmelman

Bibliographic record

VenueLimnology and Oceanography · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsUniversité Laval
FundersNational Oceanic and Atmospheric AdministrationState of Maine Department of Marine Resources
KeywordsStrongylocentrotus droebachiensisSea urchinBiologyHuman fertilizationGonadSpermPopulationFisheryEcologyZoologyBotanyAgronomyAnatomy

Abstract

fetched live from OpenAlex

During the winter and spring of 2002 and 2003, we used time-integrated fertilization assays to monitor sperm availability in three populations of the green sea urchin Strongylocentrotus droebachiensis in Maine: a naturally occurring population of >40,000 urchins and two smaller groups (<1,000) of transplanted urchins isolated from other aggregations. Episodes of sperm release coincided in two populations 10 km apart, suggesting that urchins were responding to a widespread environmental signal. We observed significant lunar periodicity in sperm release events for both of these populations. However, extensive spawning as shown by fertilization rates near 100% and a dramatic drop in gonad mass only occurred in the large natural population around the onset of thermal stratification and the spring phytoplankton bloom. By contrast, in the two small populations we observed low fertilization rates and little or no change in gonad mass. We speculate that a subset of males in these populations responded to a common external spawning signal, but that mass spawning is more likely to occur in large, dense populations where sperm concentrations reach high enough levels to trigger spawning in less responsive urchins.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.064
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.014
GPT teacher head0.200
Teacher spread0.186 · 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

Citations57
Published2006
Admission routes1
Has abstractyes

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