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Record W2133952148 · doi:10.1017/s0025315408000714

Barnacle recruitment on ice-scoured shores in eastern Canada

2008· article· en· W2133952148 on OpenAlexaffabout
Elizabeth Macpherson, Ricardo A. Scrosati, Patrick Chareka

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 institutionsSt. Francis Xavier University
Fundersnot available
KeywordsBarnacleIntertidal zoneShoreRocky shoreOceanographySeabed gouging by iceHabitatInvertebrateEstuarySea iceEcologyBayFisheryGeographyLarvaBiologyArctic ice packGeologyDrift ice

Abstract

fetched live from OpenAlex

Previous observations in the St Lawrence Estuary (eastern Canada) suggested that larvae of intertidal barnacles ( Semibalanus balanoides ) would settle almost exclusively inside crevices on shores that are scoured by sea ice every winter. It was suggested that the strong ice scour in winter on that coast (which removes organisms outside of crevices) would select for such a larval behaviour. We tested the generality of this pattern by sampling other ice-scoured shores within the Gulf of St Lawrence system. In particular, we surveyed a shore in Nova Scotia where exposed habitats (subjected to strong ice scour in winter) are interspersed with sheltered habitats (which suffer milder ice scour). Such a topographical complexity might allow for the coastal larval pool to contain a proportion of larvae that have no particular settlement preference for crevices, as selective pressures for such a behaviour would be minimal in ice-sheltered habitats. Consistently with this notion, barnacle recruits (which appear after the winter ice melts) occurred abundantly both inside and outside of crevices across the shore in the spring seasons of 2005 and 2006. Average recruit density on rocky surfaces ranged between 337 and 588 recruits dm −2 , depending on the habitat. It is therefore possible that barnacle recruitment patterns on ice-scoured shores may be affected indirectly by the structural complexity of the coast.

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 score0.098
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.069
GPT teacher head0.236
Teacher spread0.167 · 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

Citations16
Published2008
Admission routes2
Has abstractyes

Explore more

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