MétaCan
Menu
Back to cohort
Record W2150543332 · doi:10.1676/02-095

DO TWO MURRELETS MAKE A PAIR? BREEDING STATUS AND BEHAVIOR OF MARBLED MURRELET PAIRS CAPTURED AT SEA

2003· article· en· W2150543332 on OpenAlexaff
Laura A. McFarlane Tranquilla, Peggy Yen, Russell W. Bradley, Brett A. Vanderkist, David B. Lank, Nadine Parker, Mark C. Drever, Lynn W. Lougheed, Gary W. Kaiser, Tony D. Williams

Bibliographic record

VenueThe Wilson Bulletin · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsNature Conservancy of CanadaUniversity of GuelphSimon Fraser UniversityStatistics CanadaCanadian Forest Service
FundersNational Council for Air and Stream Improvement
KeywordsMarbled meatNest (protein structural motif)Seasonal breederBreeding pairZoologyFisheryBiologyEcologyDemographyAnimal sciencePopulation

Abstract

fetched live from OpenAlex

Marbled Murrelets (Brachyramphus marmoratus) observed at sea usually are in pairs throughout the year. Although it has been assumed that these pairs are mates, this assumption has not been formally examined. Using data from three study sites during the breeding seasons of 1997–2001, we found that 92% of the birds that were paired at capture were of male-female pairs, and that paired females were more likely (73%) to be producing eggs than were single females (8%). Fourteen of fifteen pairs were tracked to a single nest location per pair. No pair members caught at sea were found breeding at separate nest sites. One pair was caught in two successive seasons, suggesting that at least some pairs are long lasting. Notably, pair members breeding together and radio tracked throughout the summer were detected without their breeding partners for 77% of the time. Thus, while pairs of Marbled Murrelets observed at sea most likely are members of a breeding pair, single murrelets observed at sea should not be assumed to be unpaired or nonbreeders.

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)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.001

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 head0.012
GPT teacher head0.227
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
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueThe Wilson BulletinSame topicAvian ecology and behaviorFrench-language works237,207