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Record W6894301061 · doi:10.5683/sp3/fs3kxq

Central East Slopes Wolf and Elk Study

2025· dataset· en· W6894301061 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTelemetryAerial surveyGlobal Positioning SystemCollarPredationHome rangeWildlife

Abstract

fetched live from OpenAlex

These are the telemetry data collected on both wolf and elk individuals as part of the Central East Slopes Wolf & Elk Study in Alberta, Canada. Elk telemetry data description: We captured adult, female elk during t using a net gun from a helicopter. Each animal was fitted with a Lotek GPS2200 collar (Lotek Wireless, Ontario, Canada) that collected locations every 2 h for up to 11 months. All procedures were approved Province of Alberta animal care permit #1432GP and Univ. of Alberta #300401-300601). Wolf telemetry data description: We captured wolves from 13 packs in 2002–2006 (pack sizes: 3–17 wolves) via helicopter net-gunning during winter months and with modified foot-hold traps during summer (University of Alberta Animal Care Protocols No. 391305, 353112, and 411601). We physically restrained wolves captured with helicopter net-gunning, whereas we either physically restrained or chemically immobilized wolves captured in traps. We fitted 13 wolves with Lotek (Lotek Engineering, Newmarket, ON, Canada) 3300Sw store-onboard GPS collars (2002–2005), and 6 wolves with Lotek 4400S remote-downloadable GPS collars (2005–2006); both collar types featured the advanced-scheduler option. We programmed collars to collect locations at 15-minute, 30-minute, 1-, 2-, 4-, or 6-hour intervals during October– April. We downloaded data from model 3300Sw collars upon retrieval via remote-release mechanism, recapture of the wolf, or when wolves were harvested by trappers. We remotely downloaded data from model 4400S collars every 1–2 weeks during aerial telemetry flights. Global Positioning System collars collected 443–6,676 locations per wolf and remained on wolves for 41–180 days. Collars recorded locations on 90% (3300Sw model) and 82% (4400S model) of fix attempts, suggesting the influence of habitat-induced GPS bias was minimal (Frair et al. 2004). Previous trials using Lotek GPS collars in our study system indicate that 95%of locations fall within 114 m of the true position, with a Bessel distribution (s parameter) of 34 m (Hebblewhite 2006)

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.927
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2025
Admission routes2
Has abstractyes

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