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Record W2105913422 · doi:10.1675/063.036.0317

Effects of Increasing Age on Fecundity of Old-aged Canada Geese (<i>Branta canadensis</i>)

2013· article· en· W2105913422 on OpenAlexaboutno aff
Michael R. Conover

Bibliographic record

VenueWaterbirds · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersUtah Agricultural Experiment Station
KeywordsFledgeFecundityBrantaBiologyBroodAvian clutch sizeReproductionPopulationHatchingEcologyHatchlingZoologyDemographyGoose

Abstract

fetched live from OpenAlex

Senescence is a decline in body function with advanced age that manifests itself in birds as a decrease in survival rates or reproduction. Senescence is difficult to study in free-ranging birds because few birds reach old age and few studies last long enough to identify those birds that do. For 21 years, I studied lifelong reproduction among Canada Geese (Branta canadensis) nesting in New Haven County, Connecticut. These data were used to determine the impact of old age on female and male fecundity during the current year and during the remainder of the birds' lives. Old-aged geese were relatively common in this population; 15% of recruited geese lived 10 years, 3% lived 15 years, and one female lived 20 years. Females that nested when they were between 5 and 9 years old had a mean clutch size of 4.5, brood size at hatching of 3.4, and brood size at fledging of 2.9. Females that nested when they were at least 10 years old had a mean clutch size of 4.7, brood size at hatching of 3.4, and brood size at fledging of 3.3. These variables were independent of age for both sexes. Future reproduction (number of future nesting years and future production of eggs, hatchlings, and fledglings) declined with parental age for males but not females. Body mass of nesting birds did not change with age for either males or females. These results provided evidence of an effect of senescence in male Canada Geese but not females. The terminal investment hypothesis (i.e., that parental investment should increase as birds become older) was not supported for either sex.

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)0.000
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 score0.906
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.004
GPT teacher head0.183
Teacher spread0.179 · 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
Published2013
Admission routes1
Has abstractyes

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