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Record W2899819315 · doi:10.1098/rspb.2018.1792

Dental ontogeny in extinct synapsids reveals a complex evolutionary history of the mammalian tooth attachment system

2018· article· en· W2899819315 on OpenAlexafffund
Aaron R. H. LeBlanc, Kirstin S. Brink, Megan R. Whitney, Fernando Abdala, Robert R. Reisz

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsUniversity of British ColumbiaUniversity of TorontoUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Investigaciones Científicas y TécnicasKillam TrustsNational Research FoundationMichael Smith Health Research BC
KeywordsDentitionBiologyNeotenyOntogenyCanine toothAnatomyTooth wearMammalEvolution of mammalsEvolutionary biologyOrthodonticsZoologyPaleontologyMedicine

Abstract

fetched live from OpenAlex

The mammalian dentition is uniquely characterized by a combination of precise occlusion, permanent adult teeth and a unique tooth attachment system. Unlike the ankylosed teeth in most reptiles, mammal teeth are supported by a ligamentous tissue that suspends each tooth in its socket, providing flexible and compliant tooth attachment that prolongs the life of each tooth and maintains occlusal relationships. Here we investigate dental ontogeny through histological examination of a wide range of extinct synapsid lineages to assess whether the ligamentous tooth attachment system is unique to mammals and to determine how it evolved. This study shows for the first time that the ligamentous tooth attachment system is not unique to crown mammals within Synapsida, having arisen in several non-mammalian therapsid clades as a result of neoteny and progenesis in dental ontogeny. Mammalian tooth attachment is here re-interpreted as a paedomorphic condition relative to the ancestral synapsid form of tooth attachment.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.006
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.032
GPT teacher head0.241
Teacher spread0.210 · 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.

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

Citations53
Published2018
Admission routes2
Has abstractyes

Explore more

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