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Record W4402320963 · doi:10.5376/ijmeb.2024.14.0019

Evolutionary Trends in Beetle Morphology Insights from Fossil Records

2024· article· en· W4402320963 on OpenAlexvenueno aff
Guanli Fu

Bibliographic record

VenueInternational Journal of Molecular Evolution and Biodiversity · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMorphology (biology)Fossil RecordEvolutionary biologyPaleontologyBiologyGeographyEcology

Abstract

fetched live from OpenAlex

This study delves into the evolutionary trends in beetle morphology, drawing extensively from fossil records to provide comprehensive insights. Key findings reveal significant morphological adaptations in beetles, such as the development of elytra, variations in mouthpart structures, and changes in limb morphology, which have enabled beetles to thrive in diverse ecological niches. The study also underscores the critical role of climatic changes, predation, competition pressures, and habitat adaptations in shaping these morphological traits. Case studies highlight unique insights, such as the evolution of hardened forewings and specialized feeding structures, emphasizing the intricate interplay between environmental factors and morphological evolution. By integrating fossil evidence with modern technological approaches, this study enhances our understanding of beetle evolutionary history and its broader implications for evolutionary biology.

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 score0.028
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.014
GPT teacher head0.231
Teacher spread0.217 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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