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Record W2134571763 · doi:10.1139/z2012-091

Female Eastern Hog-nosed Snakes (<i>Heterodon platirhinos</i>) choose nest sites that produce offspring with phenotypes likely to improve fitness

2012· article· en· W2134571763 on OpenAlexafffundvenue
Casey Peet-Pare, Gabriel Blouin‐Demers

Bibliographic record

VenueCanadian Journal of Zoology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyNest (protein structural motif)OffspringOviparityAvian clutch sizeZoologyEcologyHabitatReproductionPregnancy

Abstract

fetched live from OpenAlex

Nest-site selection is an important behaviour in oviparous reptiles because incubation conditions affect offspring phenotype, with favourable conditions leading to higher offspring fitness. We aimed to identify the habitat characteristics involved in nest-site selection in Eastern Hog-nosed Snakes ( Heterodon platirhinos Latreille, 1801) and to determine whether females select nest sites that result in offspring with phenotypes likely to improve fitness. We compared the habitat characteristics and temperature profiles of 21 nests with 21 randomly selected sites. Eastern Hog-nosed Snakes selected open, grassy sites with less herbs and shrubs than random sites, and nests were significantly warmer than random sites during the 2 years of the study. In the second year of the study, we incubated 215 eggs from eight nests in a split-clutch design at mean nest (24 °C) and random site (22 °C) temperatures approximating those of the first year of the study. Eggs incubated at 24 °C resulted in neonates that hatched earlier, had fewer scale anomalies, were larger, and swam faster than neonates from eggs incubated at 22 °C. Our results indicate that Eastern Hog-nosed Snakes select nest sites that lead to offspring with phenotypes likely to improve fitness.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.016
GPT teacher head0.210
Teacher spread0.193 · 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

Citations17
Published2012
Admission routes3
Has abstractyes

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