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Record W2051913356 · doi:10.1139/z04-002

Geographic variation in snapping turtle (<i>Chelydra serpentina serpentina</i>) egg components across a longitudinal transect

2004· article· en· W2051913356 on OpenAlexvenueno aff
Michael S. Finkler, Anthony C. Steyermark, Kate E. Jenks

Bibliographic record

VenueCanadian Journal of Zoology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
FundersUniversity of Miami
KeywordsChelydraTransectBiologyTurtle (robot)Hydric soilEcologyRange (aeronautics)LatitudeAvian clutch sizeLongitudeReproductionHabitatAnimal scienceZoologyGeography

Abstract

fetched live from OpenAlex

Common snapping turtles (Chelydra serpentina serpentina) have an extensive range across North America, inhabiting aquatic habitats in diverse thermal and hydric climates. Although geographic variation in reproductive characters such as female size, clutch size, and egg mass have been investigated, little is known about geographic variation in egg components. In this study, we examined variation in the water content, solid content, and shell mass of snapping turtle eggs from four populations dispersed along a longitudinal geographic transect (Pennsylvania, Michigan, Minnesota, and Nebraska). Initial egg mass and dry shell mass were similar among these four populations. However, water contents of eggs correlated positively with longitude, whereas dry content mass correlated negatively with longitude. Moreover, water content of eggs correlated negatively with the average number of days per year where average air temperatures exceeded 15 °C in a particular region (an indicator of regional thermal climate), and dry content of eggs correlated positively with both the number of days per year where average air temperatures exceeded 15 °C and the average total precipitation for the months of May through September (an indicator of regional hydric climate). These findings suggest that egg content (and perhaps egg quality) in this wide-ranging species of turtle varies in a manner reflecting differences in climate.

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 score0.253
Threshold uncertainty score0.976

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 head0.015
GPT teacher head0.219
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

Citations14
Published2004
Admission routes1
Has abstractyes

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