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Record W2166335044 · doi:10.1139/z03-094

Ontogenetic variation in antipredator behavior of Iberian rock lizards (<i>Lacerta monticola</i>): effects of body-size-dependent thermal-exchange rates and costs of refuge use

2003· article· en· W2166335044 on OpenAlexvenueno aff
José Martı́n, Pílar López

Bibliographic record

VenueCanadian Journal of Zoology · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyPredationJuvenileOntogenySauriaLizardPredatorThermoregulationEcologyLacertidaeEscape responseZoologySquamataAffect (linguistics)

Abstract

fetched live from OpenAlex

In lizards, ontogenetic changes in body size affect thermal-exchange rates. This simple physical property may have consequences for thermoregulation, and also for antipredator behavior. We examined how ontogenetic changes in body mass affect rates of heating and cooling of the lizard Lacerta monticola, confirming the general result obtained for other lizards. We further analyzed the differences between juveniles and adults in approach distances to a simulated predator and in time to emerge from refuges. Juvenile lizards have a lower absolute running speed, making them more vulnerable to predation. However, in contrast to results expected from optimal-escape theory, approach distances were shorter for juveniles than for adults. Juveniles may be confident in their small size and only flee when the probability of being detected is high. On the other hand, differences in thermal properties might affect costs of refuge use. Thus, juveniles might delay fleeing because their costs of hiding are higher, as they cool faster than adults. Differences in thermal costs may also explain the juveniles' shorter times of emergence from refuges. Because of the behavioral adjustments involved in antipredator behavior, the physiological costs of reaching a low body temperature in refuges probably do not differ between age classes.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.217
Teacher spread0.205 · 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

Citations65
Published2003
Admission routes1
Has abstractyes

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