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Record W3201996957 · doi:10.1002/jmor.21417

The hybrid skull of the eastern coyote (<i>Canis latrans</i> var.): Nonmetric traits and craniomandibular shape

2021· article· en· W3201996957 on OpenAlexafffund
Natasa Zdjelar, Lavania Nagendran, Christopher Kendall, R. Ackermann, Lauren Schroeder

Bibliographic record

VenueJournal of Morphology · 2021
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsRoyal Ontario MuseumUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaConnaught FundNational Research Foundation
KeywordsBiologySkullSupernumeraryHybridCanisAllometryZoologyEvolutionary biologyAnatomyEcology

Abstract

fetched live from OpenAlex

The increasing awareness that hybridization, and resultant gene flow, plays a major role in animal diversification has led to a growing number of studies that have focused on assessing the morphological consequences of this process. Analyses of mammalian hybrids have identified skeletal effects of hybridization, including a suite of anomalous dental and sutural traits on the skull that are present at high frequencies in hybrid populations. These studies have also detected consistent patterns of morphological shape and size differences between hybrids and parental taxa across a wide variety of organisms. However, more research is required to understand the universality of these traits and shape/size differences. Building on these previous studies, a sample of genetically determined canid hybrids was examined, specifically the eastern coyote (Canis latrans var.), a hybrid between coyotes, wolves, and dogs, to test whether this group exhibits a comparable pattern of anomalous nonmetric characters, and to assess differences in craniomandibular shape and size. First, specimens of C. latrans var., C. latrans, and C. lupus were scored for anomalous traits, including supernumerary and rotated teeth, dental crowding, and sutural anomalies. Geometric morphometric analyses were then conducted on a subset of these individuals to explore craniomandibular size and shape variation, as well as allometry. The results are largely consistent with other studies, indicating that the incidence of dental anomalies, dental crowding, and sutural anomalies is significantly higher in hybrids. However, differences are not significant for supernumerary teeth. The exploration of morphometric variation identifies intermediate morphology in the hybrids, and some indication of greater morphological variability in the mandible. When these results are combined with previous studies, they suggest that skeletal signatures of hybridization are common to different mammalian taxa across multiple generations; however, some traits such as supernumerary teeth may be lost after a few generations.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.024
GPT teacher head0.259
Teacher spread0.235 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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