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Chronology of Breeding and Molt Migration in Surf Scoters (Melanitta perspicillata )

2007· article· en· W2151266606 on OpenAlexaffabout
Jean‐Pierre L. Savard, Austin Reed, Louis Lesage

Bibliographic record

VenueWaterbirds · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsBroodChronologySeasonal breederEcologyBiologyHabitatZoologyMoultingGeographyLarva

Abstract

fetched live from OpenAlex

Little is known about the molt migration of the Surf Scoter (Melanitta perspicillata), a species endemic to North America. Our objective in this study was to document the breeding and molting chronology of Surf Scoters in Québec. Breeding birds were studied at Lake Malbaie, located about 90 km north of Québec City, Canada. Surf Scoters arrived at Lake Malbaie in the fourth week of May and most males stayed only for approximately three weeks. This relatively early departure of males from the breeding areas emphasizes the importance of salt water habitats for these birds. Unsuccessful adult females did not leave with the males but remained on their breeding lake. These females left the lake from mid to late July, nearly a month after the departure of males and much earlier than females with broods which left from mid to late August after abandoning their brood. This departure sequence was observed during the three years of the study. The difference in timing of molt migration between age and sex groups has important management implications as it potentially exposes them to different levels of mortality. For example, late molters, mostly adult females that bred successfully may still be flightless at the beginning of the hunting season in some areas. Better understanding of molt chronology and habitat selection by various sex and age groups will permit a more holistic and efficient management of Surf Scoters.

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 score0.368
Threshold uncertainty score0.732

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.228
Teacher spread0.219 · 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

Citations20
Published2007
Admission routes2
Has abstractyes

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