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Record W2765810815 · doi:10.5038/2074-1235.38.1.875

Modified Hoop-net Techniques for Capturing Birds at Sea and Comparison with Other Capture Methods

2010· article· en· W2765810815 on OpenAlex
Robert A. Ronconi, Zachary T. Swaim, H. Clifford Lane, Robin W. Hunnewell, A. Westage, Heather N. Koopman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMarine ornithology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie UniversityUniversity of North Carolina WilmingtonU.S. Fish and Wildlife ServiceKillam TrustsBird Studies Canada
KeywordsSeabirdOrnithologyEnvironmental scienceOceanographyFisheryEcologyBiologyGeologySouthern Hemisphere

Abstract

fetched live from OpenAlex

From 2005 to 2008 we developed modified hoop-nets to capture Great and Sooty shearwaters Puffinus gravis and P. griseus, and Red-necked and Red phalaropes Phalaropus lobatus and P. fulicarius in the Bay of Fundy, Canada.Hoop-nets allowed daytime captures of more than 200 Great Shearwaters (average 3.4 birds per trip) but only 6 Sooty Shearwaters (0.1 birds per trip) without chumming.Sooty Shearwaters were captured more effectively at night using spotlights and dip-nets (approximately 1.8 birds per trip).Phalaropes (n = 17) were captured at night using spotlights and a lighter hoop-net.We caught 1.5 phalaropes per trip on average (range 0 to 8 individuals).We discuss the limitations of each technique and review reported methods used to capture other species-floating and submerged mist-nets, net-guns, castnets, spotlighting, and other hoop-nets.The main advantage of our technique is the ability to catch shearwaters without chumming.It is the only known method for capturing phalaropes at sea.Techniques described here and other at-sea capture methods allow investigators to address new questions about seabird ecology.

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.

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 score0.171
Threshold uncertainty score0.996

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 science0.0000.001
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 head0.015
GPT teacher head0.285
Teacher spread0.270 · 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