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Record W7125686318 · doi:10.64555/0grdmz91

Changes in Regional Winter Abundance of the Golden-crowned Sparrow Revealed by Christmas Bird Count Data

2024· article· W7125686318 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCentral Valley Birds · 2024
Typearticle
Language
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersU.S. Geological SurveyU.S. Fish and Wildlife ServiceMinistry of EnvironmentBird Studies Canada
KeywordsSparrowAbundance (ecology)Range (aeronautics)Distance samplingRelative species abundanceSeasonal breederPopulationCount data

Abstract

fetched live from OpenAlex

Assessing trends in abundance of bird species whose breeding range is poorly sampled by Breeding Bird Surveys poses significant challenges. The Golden-crowned Sparrow (Zonotrichia atricapilla) is one such species. Range-wide data from the Christmas Bird Count (CBC) can be used to assess trends in this species’ winter abundance and, by inference, range-wide breeding population trends. We used CBC data from throughout the winter range of the Golden-crowned Sparrow over the 40 years from 1984–2023 to assess abundance trends. Our analysis suggests that the overall population is stable, but that numbers are increasing significantly at the northern edge of the winter range, and declining significantly at the southern edge, suggesting a poleward shift in relative abundance in recent decades. Increases in winter temperatures throughout this species’ winter range may be a key driver of this northward shift either through changes in over-winter survival, breeding season productivity, or both.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.033
GPT teacher head0.261
Teacher spread0.228 · 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