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Record W2924550113 · doi:10.36967/2301061

Moose (Alces alces) population survey in Yukon-Charley Rivers National Preserve, November 2022

2023· report· en· W2924550113 on OpenAlexaboutno aff
Matthew Sorum, Jordan Pruszenski, Kyle Joly, Matthew D. Cameron

Bibliographic record

VenueNational Park Service · 2023
Typereport
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyPopulationAnimal scienceSurvey researchBiologyDemographySocioeconomics

Abstract

fetched live from OpenAlex

Overall survey dates: November 6-19, 2022 (10 days of survey, 3 weather days) Total survey area: 3,096 mi2 (8,018 km2), 555 survey units Area surveyed: 614 mi2 (1,590 km2), 110 survey units Total moose observed: 183 (101 cows, 21 calves [2 set of twins], 61 bulls) Average search effort: 5.9 minutes/mi2 (3.5 minutes/km2) Population estimate: 738 moose (90% CI: 548-928; +/-26%); long-term average 848 moose Estimated density: 0.24 moose/mi2 (0.62 moose/km2); long-term average 0.27 moose/mi2 Estimated age/sex ratios: 19 calves:100 cows, 7 yearlings bulls:100 cows, 60 bulls:100 cows

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.142
GPT teacher head0.337
Teacher spread0.195 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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