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Record W2184067800 · doi:10.5038/2074-1235.42.2.1076

Coastal Dispersal by Pre-breeding African Black Oystercatchers Haematopus Moquini

2014· article· en· W2184067800 on OpenAlexfundno aff
Anuradha Shakuntala Rao, Peter Hockey, WA Montevecchi

Bibliographic record

VenueMarine ornithology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersUniversity of Cape TownNatural Sciences and Engineering Research Council of CanadaMemorial University of NewfoundlandNational Research Foundation
KeywordsOrnithologySeabirdBiological dispersalGeographyBiologyEcologyFisherySouthern HemisphereDemography

Abstract

fetched live from OpenAlex

African Black Oystercatcher Haematopus moquini high-tide roost sites were located and mapped along the Atlantic coasts of South Africa and Namibia.Nearly all roosts checked contained juvenile and/or immature, individually colour-banded birds.A series of dispersal roosts were identified along the coastline, with the largest roosts being in central Namibia.Birds forage at or near the roost sites at low tide.Of birds banded in southwestern South Africa with confirmed dispersal endpoints, 65% dispersed north of Lüderitz, Namibia (average travel distance of 1 595 km from natal site), 11% dispersed to northwestern South Africa (average travel distance 548 km), 19% dispersed within southwestern South Africa (average travel distance 141 km), and 5% dispersed eastward along the south coast of South Africa (average travel distance 237 km).At least 22% of re-sighted birds departed in their first year of life, and 25% returned in their third or fourth year of life.Body condition, sex and relative hatch date were not associated with roost site distances from natal colonies.Dispersal connectivity is weak in this species, as immature birds of different ages and origins mixed at roost sites along the dispersal route.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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