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Record W4252527259 · doi:10.1093/condor/107.4.898

Mallard Duckling Survival in the Great Lakes Region

2005· article· en· W4252527259 on OpenAlexaff
John Simpson, Tina Yerkes, Barry D. Smith, Thomas D. Nudds

Bibliographic record

VenueOrnithological Applications · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of GuelphEnvironment and Climate Change Canada
Fundersnot available
KeywordsAnasWaterfowlHatchingAnatidaeTemperate climateEcologyBiologyBroodMortality rateOverwinteringGeographyDemographyHabitat

Abstract

fetched live from OpenAlex

Abstract Survival of young in waterfowl is poorly understood, particularly in regions outside of the traditional prairie breeding areas. Further, traditional methods of survival estimation lack the ability to statistically characterize between the extremes of random and catastrophic mortality events. We estimated Mallard (Anas platyrhynchos) duckling survival rates for 121 broods at nine study sites across the Great Lakes region from 2001–2003, using a novel statistical method that allows for the partitioning of random and correlated mortality processes. Results indicated that survival increased rapidly with age, did not change with hatching dates, did not differ among years, but varied across site-by-year replicates. Rates of random mortality were found to vary among site-years, while rates of correlated mortality varied little across site-years. In contrast to most studies of Mallard duckling survival, seasonal increases in duckling survival were not detected. We speculate that the observed patterns in survival rates with hatching date are related to productivity in Great Lakes brood-rearing wetlands and temperate regional climate.

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)0.001
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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.033
GPT teacher head0.267
Teacher spread0.234 · 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

Citations10
Published2005
Admission routes1
Has abstractyes

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