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Record W3006281761 · doi:10.1139/cjz-2019-0238

Demographics of injuries indicate sexual coercion in a population of Painted Turtles (<i>Chrysemys</i> <i>picta</i>)

2020· article· en· W3006281761 on OpenAlexaffvenue
Patrick D. Moldowan, Ronald J. Brooks, Jacqueline D. Litzgus

Bibliographic record

VenueCanadian Journal of Zoology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsUniversity of GuelphLaurentian University
Fundersnot available
KeywordsPainted turtleBiologyCourtshipMatingPopulationZoologySexual coercionDemographicsDemographyTurtle (robot)EcologyPoison controlInjury prevention

Abstract

fetched live from OpenAlex

Sexually coercive reproductive tactics are widespread among animals. Males may employ specialized structures to harass, intimidate, or physically harm females to force copulation, and injuries to the head and neck are reported in taxa with sexually coercive mating systems. The mating tactics of Painted Turtles (Chrysemys picta (Schneider, 1783)) are typically described as involving male courtship and female choice. In contrast, female Painted Turtles in our study population display injuries on the head and neck indicative of bite wounds inflicted by sexually dimorphic tomiodonts and weaponized shell morphology of males during reproductive interactions. Using a 24-year data set, we demonstrate population-level trends in soft tissue wounds inflicted by conspecifics. Adult females experienced more wounding than adult males or juveniles, and larger females had a greater probability of wounding than smaller females. Wounding was concentrated on the dorsal head and neck of females, consistent with expectation of sexual coercion. Furthermore, elevated rates of fresh wounding occurred during late summer, concurrent with the breeding period. By assessing wound demographics, we provide indirect evidence that the tomiodonts and shell of male Painted Turtles inflict injury and function as sexual weapons. These findings shed new light on our understanding of mating system complexity in an often-overlooked and difficult-to-observe taxonomic group.

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 score0.047
Threshold uncertainty score0.965

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 head0.012
GPT teacher head0.202
Teacher spread0.190 · 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

Citations12
Published2020
Admission routes2
Has abstractyes

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