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Notes on Split Clutch Nesting and Supernumerary Nests in the Mountain plover

2025· article· W4416380136 on OpenAlexaff
Alex Blanche, Avalon Faticoni-Manolas, Casey Weissburg, Michael B. Wunder

Bibliographic record

Venuenot available
Typearticle
Language
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsPloverAvian clutch sizeNesting (process)ClutchBreeding pairNest (protein structural motif)

Abstract

fetched live from OpenAlex

Clutch size is traditionally defined as the number of eggs laid by a mated pair in a single breeding attempt. Some avian species increase reproductive output by splitting the breeding attempt across multiple nests that are simultaneously and independently incubated by either the male or the female. In this paper, we define a “clutch” for species with such split clutch nesting as the sum of eggs laid in rapid succession across two or more nest cups in a single breeding attempt and introduce the term “split-clutch” for the fraction of the clutch laid in a single nest cup. We then report cases of supernumerary split-clutches in the mountain plover, a species known to use this strategy. The case of a 10-egg nest represents the largest split-clutch observed in this species. We discuss hypothetical explanations for supernumerary nests in species with split clutch nesting, considering physiological limitations as well as potential for parasitism. We conclude that our observation of a 10-egg split-clutch either increases the known physiological limit for a single laying female or establishes a record of parasitism in the mountain plover. Further documentation of parentage of supernumerary split-clutches is warranted.

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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.262
Teacher spread0.248 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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