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Record W2095394445 · doi:10.1139/z10-087

Nutritional importance of seeds and arthropods to painted spiny pocket mice (Lyomis pictus): the effects of season and forest degradation

2010· article· en· W2095394445 on OpenAlexvenueno aff
Gustavo Ramírez-Hernández, L. Gerardo Herrera M.

Bibliographic record

VenueCanadian Journal of Zoology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyDry seasonWet seasonHoarding (animal behavior)FrugivoreEcologyTrophic levelTropical and subtropical dry broadleaf forestsDetritivoreBiomass (ecology)Gallery forestHabitatForaging

Abstract

fetched live from OpenAlex

Temporal and spatial fluctuations in food abundance may affect the feeding habits of vertebrates in tropical dry forests. We explored the effects of season and forest degradation in dietary patterns of the painted spiny pocket mouse ( Lyomis pictus (Thomas, 1893)) (Heteromyidae) in a Mexican tropical dry forest. We used carbon (13C,12C) and nitrogen (15N,14N) stable isotope analyses to test the hypotheses that (i) L. pictus would increase its use of arthropods during the rainy season when seeds are less available on the forest floor and (ii) that L. pictus would increase its use of arthropods in degraded forest compared with conserved forest. Our hypotheses were wrong because assimilated biomass was derived almost exclusively from seeds in both seasons and the importance of arthropods was marginal in both sites. Examination of food remains in feces and cheek pouches confirmed these trophic patterns. Seed hoarding during the season of high seed availability probably allows L. pictus to subsist on a seed-based diet throughout the year in conserved and disturbed forests. This behavioral trait would enable L. pictus to maintain its specialized feeding habit in environments threatened by habitat degradation.

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 score0.006

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 head0.005
GPT teacher head0.213
Teacher spread0.208 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

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