MétaCan
Menu
Back to cohort
Record W4414533056 · doi:10.1002/ajpa.70131

Dental Microwear and Diets of Late Miocene Primates From Rudabánya, Hungary

2025· article· en· W4414533056 on OpenAlexaff
Peter S. Ungar, Anna K Wilcox, David R. Begun

Bibliographic record

VenueAmerican Journal of Biological Anthropology · 2025
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsUniversity of Toronto
FundersUniversity of Arkansas
KeywordsLate MioceneNicheTexture (cosmology)Hominidae

Abstract

fetched live from OpenAlex

OBJECTIVES: This study focuses on a dental microwear texture analysis of European pliopithecids and dryopithecins from the Miocene primate site of Rudabánya, Hungary. The goal is to determine whether these taxa, found in part together in the same deposits, differed in their food preferences, or at least consumed, on a daily basis, in a manner that might have facilitated sympatry. MATERIALS AND METHODS: Here we report on a molar surface texture analysis of all available fossil primates from Rudabánya that preserve antemortem microwear. This includes both Anapithecus hernyaki (n = 14) and Rudapithecus hungaricus (n = 5, including one from Alsótelekes). Scanning confocal profilometry was used to generate point clouds, and texture complexity and anisotropy values were compared between the fossil taxa and contextualized with published data for an extant baseline series. RESULTS: Texture complexity and anisotropy values for both samples fall within the range of extant frugivorous primates. Further, while anisotropy does not differ between the fossil taxa, Rudapithecus has a significantly higher complexity average than Anapithecus. DISCUSSION: The difference in microwear texture complexity suggests that Rudapithecus individuals studied here consumed harder foods on average than did Anapithecus individuals did. This is consistent with the notion that dietary differences may have played a role in the niche separation of these taxa.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.342
Teacher spread0.323 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Biological AnthropologySame topicPrimate Behavior and EcologyFrench-language works237,207