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Record W573433825 · doi:10.15094/00006213

Seasonal scatology of wolves along the Dempster Highway, northwestern Canada-an introduction of pollen analysis for dating old scats

2004· article· en· W573433825 on OpenAlexfundaboutno aff
Sayoko Ueda, Naoko Sasaki, Tatsuo Sweda

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsnot available
FundersCanadian Forest ServiceU.S. Forest ServiceUniversity of AlbertaParks Canada
KeywordsPollenGeographyArchaeologyEcologyBiology

Abstract

fetched live from OpenAlex

This study aims to renovate the method of studying seasonal variation in wolf diet by introducing simultaneous analysis of undigested residua and pollen grains in wolf scats collected regardless of their freshness over a short period of time, in which pollen grains help to identify the season the diet was taken. The present study was conducted over a range of 500 km along the Dempster Highway extending north from Dawson, Yukon Territory to Inuvik, the Northwest Territories, Canada. We collected a total of 24 wolf scats along side roads and rivers, in which as many as 14 million pollen grains/scat were found on an average. The analysis revealed that the wolves relied exclusively on the caribou during winter when scats are free of pollen grains, but increase their dependence on the beaver and other mammals up to over 50% in term of residuum occurrence in spring and summer when scats are respectively loaded primarily with arboreal and herbaceous pollen grains. This result was consistent with the local fauna of prey animals, the migration pattern of the caribou for breeding and wintering, availability of the beaver and other rodents as dictated by ice/snow cover, and breeding and cub rearing pattern of the wolves themselves. Thus it was concluded that the pollen analysis serves as a powerful and effective tool for identifying the seasonality of old scats, and therefore saves a great deal of time and effort to be devoted to finding fresh scats.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.530
Threshold uncertainty score0.736

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.286
Teacher spread0.264 · 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 teacher head, 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
Published2004
Admission routes2
Has abstractyes

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Same venueInstitutional Repositories DataBase (IRDB)Same topicPleistocene-Era Hominins and ArchaeologyFrench-language works237,207