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Record W1986515397 · doi:10.1139/z06-040

Cost of foraging in the subterranean rodent<i>Ctenomys talarum</i>: effect of soil hardness

2006· article· en· W1986515397 on OpenAlexvenueno aff
Facundo Luna, C. Daniel Antinuchi

Bibliographic record

VenueCanadian Journal of Zoology · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDiggingBurrowBiologyForagingEcologyGeography

Abstract

fetched live from OpenAlex

Subterranean burrows provide inhabitants with shelter, a relatively stable thermal environment, and potentially access to food resources. However, one cost of living in such burrows is the energetically expensive mode of locomotion. Soil hardness and the physiological capabilities of animals are likely important factors that affect the cost of burrow construction, and hence, distribution of burrows. We assessed the effect of soil hardness on the cost of digging by captive individual Ctenomys talarum Thomas, 1898 in soft soils. Digging metabolic rate (DMR) was higher in harder soil than in softer soil (408.30 ± 51.35 mL O 2 ·h –1 vs. 267.59 ± 20.97 mL O 2 ·h –1 , respectively). In C. talarum, a higher soil hardness augments DMR by increasing, in terms of the cost of burrowing model, the costs of shearing and of pushing the removed soil. Additionally, these costs differ between C. talarum and other subterranean species (e.g., Thomomys bottae (Eydoux and Gervais, 1836)), depending on soil hardness and digging mode. Thus, the relationship between digging cost and soil hardness appears to be one of the most important factors that affect burrowing efficiency in subterranean rodents.

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 score0.551
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.206
Teacher spread0.188 · 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

Citations82
Published2006
Admission routes1
Has abstractyes

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