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Record W2068047578 · doi:10.1139/cjz-79-12-2228

Movement patterns of male common voles (<i>Microtus arvalis</i>) in a network of Y junctions: role of distant visual cues and scent marks

2001· article· en· W2068047578 on OpenAlexvenueno aff
Alexandre Dobly

Bibliographic record

VenueCanadian Journal of Zoology · 2001
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyMicrotusArvicolinaeSensory cueZoologyNeuroscienceCommunicationEcologyAnatomyPsychology

Abstract

fetched live from OpenAlex

Common voles (Microtus arvalis) use networks of runways around their burrows, which are dug in meadows. Their orientation among such networks could be based on rigid "egocentred" routes (possibly through the use of olfactory "trails") or on more general, "allocentred" spatial representations (with distant visual cues). In this 5-day study, male voles should reach food in the centre of a maze of three-way (Y) junctions offering similar local views but surrounded by distant visual cues. I tested whether the animals navigated using olfactory trails, implying one main direct foraging route, or allocentered representations, allowing flexibility among equivalent routes. Males quickly marked their environment, preferentially at the periphery, where they moved the most. However, during most direct trips between the nest and the food, they used one of the central shortest routes, which included the least scent-marked zones. Moreover, the voles preferred different shortest routes to go to the food and return from it, showing a bias in favour of the side where the distant goal (food or nest) was situated. This suggests that male common voles base their choices on the general direction of their goal rather than on trails. Finally, there was no major difference in initial exploration between a clean and a scent-marked maze.

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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.252
Teacher spread0.230 · 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

Citations12
Published2001
Admission routes1
Has abstractyes

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