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Record W1564573949

Patterns of distribution and abundance of Greater Snow Geese on Bylot Island, Nunavut, Canada 1983-1998

2014· article· en· W1564573949 on OpenAlexaboutno aff
Austin Reed, Robert Hughes, Hugh Boyd

Bibliographic record

VenueWildfowl (Wildfowl & Wetlands Trust) · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSnowGeographyArcticAbundance (ecology)Distribution (mathematics)Physical geographyAerial surveyEcologyBiologyMeteorologyCartography
DOInot available

Abstract

fetched live from OpenAlex

To m onitor the num bers and distribution of Greater Snow Geese at the largest breeding colony in the eastern Canadian High Arctic, surveys were conducted on Bylot Island at five year intervals from 1983 to 1998.The surveys were conducted during the brood-rearing period using a stratified sam pling procedure and aerial photog raphy.The total num ber of adult geese increased from 25,500 (SE 2582) in 1983 to 69,500 [SE 8645) in 1993 (a year of exceptionally high breeding effort and breeding success) before dropping slightly in 1998.The num ber of goslings also increased from 26,500 (SE 2320) in 1983 to 86,500 (SE 8147) in 1993, and also dropped slightly in 1998.In years of high breeding success (1983 and 1993) the adult popu lation on Bylot Island represented 14% of the entire world population of Greater Snow Geese.The adult population on Bylot Island between 1983 and 1998 showed an aver age annual rate of increase of 7%, sim ila r to the 9% increase recorded for the entire population.Brood densi ties varied from a low of 0.8 broods km 2 in the poorest quality habitats in 1983 to 29.9 broods k rrf2 in the best habitats in 1993, but an increasing trend was evident in all habitat strata over the course of the study.A large proportion (63%) of the surface area of the colony accommodated only very low brood densities in 1983, but by 1993 the proportion occu * .

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.005
GPT teacher head0.180
Teacher spread0.175 · 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.

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

Citations30
Published2014
Admission routes1
Has abstractyes

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