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Record W2085476481 · doi:10.1139/z03-209

Influence of egg aggregation and soil moisture on incubation of flexible-shelled lacertid lizard eggs

2004· article· en· W2085476481 on OpenAlexvenueno aff
Adolfo Marco, Carmen Díaz‐Paniagua, Judit Hidalgo-Vila

Bibliographic record

VenueCanadian Journal of Zoology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsnot available
Fundersnot available
KeywordsHatchlingBiologyIncubationHatchingNest (protein structural motif)LizardOviparityWater contentSoil waterEgg incubationEcologyBird eggAnimal science

Abstract

fetched live from OpenAlex

Many oviparous terrestrial species deposit flexible-shelled eggs into the soil. These eggs are sensitive to the hydration level of the nest environment. Among other factors, water exchange of eggs during incubation may be affected by the soil water potential. To evaluate whether egg aggregation influences embryonic development, we incubated flexible-shelled Schreiber's green lizard (Lacerta schreiberi) eggs under three levels of soil water potential (wet: –150 kPa; intermediate: –650 kPa; dry: –1150 kPa) and under two levels of aggregation (aggregated: in groups of six eggs with physical contact among them; isolated: groups of six eggs each 1 cm apart). The availability of water during egg incubation influenced egg mass and hatchling size. Eggs incubated in dry soils absorbed less water and produced smaller hatchlings. The selected levels of soil water potential did not influence incubation duration or hatching success. When soil was wet or dry, we did not find any effect of egg aggregation in embryonic development. However, when soil water potential was intermediate, aggregated eggs absorbed less water and their embryos hatched at smaller sizes compared with isolated eggs. Moreover, variability and range of egg water absorption and hatchling size were higher among aggregated eggs than among solitary ones when access to water was restricted. In these cases, eggs competed with different success for water, a limited resource in the nest environment.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.985

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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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

Citations44
Published2004
Admission routes1
Has abstractyes

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