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Phenotypic effects on survival of neonatal northern watersnakes <i>Nerodia sipedon</i>

2005· article· en· W2009985053 on OpenAlexafffund
Kelley J. Kissner, Patrick J. Weatherhead

Bibliographic record

VenueJournal of Animal Ecology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsCarleton UniversityAlberta Environment and Protected Areas
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHibernation (computing)BiologyOffspringReproductionZoologyDemographyAnimal scienceEcologyPregnancy

Abstract

fetched live from OpenAlex

Summary Understanding the trade‐off females make between offspring size and number requires knowing how neonatal size, and traits associated with size, affect survival. We studied neonatal survival in the northern watersnake Nerodia sipedon in outdoor enclosures with artificial hibernation sites. From a total of 950 neonates from 77 litters collected over 3 years, we found a survival rate of 65% between birth and hibernation and 47% during hibernation. Estimated survival from birth to the end of hibernation was 31%, comparable with indirect estimates for free‐living watersnakes. Consistent with the ‘bigger is better’ hypothesis, larger neonates and neonates heavier relative to their body length were more likely to survive both the pre‐hibernation and hibernation periods. Survival in the pre‐hibernation period also decreased with the duration of that period and varied among years. Survival during hibernation was higher in warmer winters. Mass change prior to hibernation did not affect survival during hibernation. These results suggest that an optimal reproductive strategy should exist for female watersnakes, producing a ‘consensus’ among females on the optimal size for offspring. This expectation stands in stark contrast to the pronounced variation in offspring size observed both within and among litters.

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 score0.020
Threshold uncertainty score0.943

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)0.0010.000

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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

Citations64
Published2005
Admission routes2
Has abstractyes

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