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Record W2515566169 · doi:10.14430/arctic4575

Nesting Activity of Kittlitz’s Murrelet in the Kakagrak Hills, Northwestern Alaska

2016· article· en· W2515566169 on OpenAlexvenueno aff
Michelle L. Kissling, Stephen B. Lewis

Bibliographic record

VenueARCTIC · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceNational Park ServiceUniversity of Montana
KeywordsNest (protein structural motif)EcologyTransectGeographySeabirdHabitatRange (aeronautics)BiologyPredation

Abstract

fetched live from OpenAlex

The Kittlitz’s Murrelet (Brachyramphus brevirostris) is a broadly distributed but uncommon seabird species endemic to coastal Alaska and eastern Russia. Although northern Alaska constitutes a large portion of this species’ range, little is known about Kittlitz’s Murrelets in this vast region. We studied nesting activity of Kittlitz’s Murrelets in the Kakagrak Hills, Cape Krusenstern National Monument, in northern Alaska during summer 2014. Between 15 and 26 June, we located two active Kittlitz’s Murrelet nests by walking line transects in 28 sampling blocks (250 × 250 m) that were stratified by two habitat types (Alpine Alkaline Barrens and Alpine Dryas Dwarf Shrub) and selected randomly. We found one additional active nest opportunistically while walking between blocks. All three nests were located in Alpine Alkaline Barrens habitat, and all failed during the egg stage. Causes of failure were nest abandonment (n = 1), depredation (n = 1), and unknown (n = 1). Overall mean nest density was 0.80 nests/km2 (SE = 0.52). Although our sample of nests was small, our results demonstrate that Kittlitz’s Murrelets nest regularly in northern Alaska. However, the apparently low productivity raises questions about the reproductive value of this region to this cryptic and secretive species.

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 score0.021
Threshold uncertainty score0.533

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 head0.230
Teacher spread0.216 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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Same venueARCTICSame topicAvian ecology and behaviorFrench-language works237,207