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Record W4220917781 · doi:10.1676/20-00125

Preformative molt, plumage maturation, and age criteria for 7 species of manakins

2021· article· en· W4220917781 on OpenAlexaff
Micah N. Scholer, Jeremiah C. Kennedy, Blaine H. Carnes, Jill E. Jankowski

Bibliographic record

VenueThe Wilson Journal of Ornithology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsPlumageBiologyZoologyFeatherMorphometricsEcology

Abstract

fetched live from OpenAlex

We developed aging criteria for 7 species of manakins (Pipridae) from the Manu Biosphere Reserve, Peru, based on patterns of plumage maturation and wing-feather replacement following their preformative molt, and summarize information on their morphological characteristics. Each species underwent a partial preformative molt, which could be identified using the presence of molt limits in the greater coverts. Some male Band-tailed Manakin (Pipra fasciicauda), Round-tailed Manakin (Ceratopipra chloromeros), Cerulean-capped Manakin (Lepidothrix coeruleocapilla), and Yungas Manakin (Chiroxiphia boliviana) showed evidence of delayed plumage maturation, allowing for age classification up to the third annual cycle, whereas Blue-crowned Manakin (L. coronata caelestipileata), Fiery-capped Manakin (Machaeropterus pyrocephalus), and Green Manakin (Cryptopipo holochlora viridor) appeared to attain definitive plumage after their second molt cycle. Morphometrics showed strong overlap and were less useful for separation of age and sex classes. Our findings add to the growing list of studies that suggest many tropical passerines can be aged using primarily molt limits. Data on molt and plumage maturation are still needed for the vast majority of tropical birds in order to inform conservation-based research and studies of avian life history.

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 score0.471
Threshold uncertainty score0.928

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)0.0010.000

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 head0.025
GPT teacher head0.279
Teacher spread0.255 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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