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Record W1504501502 · doi:10.22621/cfn.v126i2.1332

Size of Territories and Home Ranges of Male Western Yellow-breasted Chats (<em>Icteria virens auricollis</em>) in British Columbia

2012· article· en· W1504501502 on OpenAlexafffundvenueabout
René McKibbin, Christine A. Bishop

Bibliographic record

VenueThe Canadian Field-Naturalist · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsEnvironment and Climate Change Canada
FundersSimon Fraser University
KeywordsHome rangeTelemetryBiologyGeographySingingZoologyEcologyTelecommunicationsHabitatPhysicsComputer science

Abstract

fetched live from OpenAlex

During 2005 and 2006, radio-transmitters were fitted to a total of 11 male Western Yellow-breasted Chats, Icteria virens auricollis, in the southern Okanagan River valley, British Columbia, to compare the area used, as detected by radio-telemetry and as defined by mapped observations of breeding males singing and perching. Data were only collected for 5 males. For 2005 and 2006, the 95% kernel density estimation (KDE) revealed that mean area used by male Western Yellow-breasted Chats, as determined by radio-tracking (n = 5), was 1.16 ha, whereas the mean area as defined by observations of breeding males singing and perching was 0.62 ha (no statistical difference). Our hypothesis that the area determined by radio-tracking would be significantly larger than the area defined by observations of males singing and perching was rejected, but the area determined by radio-tracking was almost twice the area defined by observations of breeding males singing and perching.

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 score0.180
Threshold uncertainty score0.363

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.007
GPT teacher head0.192
Teacher spread0.184 · 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

Citations2
Published2012
Admission routes4
Has abstractyes

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