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BREEDING GROUND AFFILIATION AND MOVEMENTS OF GREATER WHITE-FRONTED GEESE STAGING IN NORTHWESTERN TEXAS

2003· article· en· W6926143850 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2003
Typearticle
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsnot available
Fundersnot available
KeywordsWaterfowlPopulationAnatidaePeriod (music)Goose

Abstract

fetched live from OpenAlex

Abstract Data from neck-band observations were used to determine breeding-ground affiliation, period of use, and winter movement patterns of greater white-fronted geese (Anser albifrons frontalis) observed in the Winchester Lakes region of northwestern Texas. Over 1,265 observations of nearly 800 individual neck-banded geese (3.2% of all neck-banded white-fronted geese in North America) were recorded in the region from 1988 through 1996. More than 4,200 observations of these individuals were recorded throughout North America. Observations peaked in November and February, indicating that the Winchester Lakes region is a migratory staging area for white-fronted geese. Only 6% of the birds in this region remained throughout the winter. Most birds staging in the Winchester Lakes region wintered in the rice prairies of coastal Texas and interior Mexico. Eighty-eight percent of the neck-banded geese were from the western portion of the midcontinent population of greater white-fronted geese, primarily representing Interior-Northwest Alaska, Yukon, and Anderson River breeding populations. These breeding populations are characterized by declining trends in population size and survival rates. The status (e.g., population trends, productivity, survival) of these breeding populations must be considered when managing birds in the Winchester Lakes region.

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 score0.040
Threshold uncertainty score0.080

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 head0.201
GPT teacher head0.250
Teacher spread0.050 · 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
Published2003
Admission routes1
Has abstractyes

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