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Record W1968043974 · doi:10.1139/z09-028

Explaining patterns of deformity in freshwater turtles using MacCulloch’s hypothesis

2009· article· en· W1968043974 on OpenAlexaffvenueabout
Christina M. Davy, Robert W. Murphy

Bibliographic record

VenueCanadian Journal of Zoology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsRoyal Ontario MuseumUniversity of Toronto
FundersSouth China University of Technology
KeywordsChelydraBiologyPainted turtleTurtle (robot)DeformityZoologyEcology

Abstract

fetched live from OpenAlex

A growing body of literature details the effects of teratogenic chemicals on embryonic development in freshwater turtles. However, other factors affecting developmental deformities have not been recently considered and evaluation of the significance of deformities in adults is lacking. We collected 193 wild Midland Painted Turtles ( Chrysemys picta marginata Agassiz, 1857) and 39 Common Snapping Turtles (Chelydra serpentina (L., 1758)) from an uncontaminated site in Ontario and recorded incidence of deformity of the shell, limbs, face, and tail. We tested MacCulloch’s hypothesis (that incidence of deformity increases along a latitudinal gradient) by comparing our data with previously published deformity records from both uncontaminated and heavily polluted sites at varying latitudes. Incidence of nonembryonic deformity varied among wild populations and was not correlated with pollution levels. Thus adult deformity cannot be used as an indicator of site quality. Frequency of deformity increased with latitude in C. picta, supporting MacCulloch’s hypothesis, whereas deformities in C. serpentina did not. We refer to essential differences in the biology of the two species to explain this disparity and recommend that latitudinal variation be included as a covariate in the future when developmental trends are compared among distant sites.

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 score0.243
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)0.0010.000

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 head0.022
GPT teacher head0.213
Teacher spread0.191 · 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

Citations20
Published2009
Admission routes3
Has abstractyes

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