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Record W4392578102 · doi:10.5194/egusphere-egu24-11329

Tectonic drivers of the scaling dinosaurian fossil record

2024· preprint· en· W4392578102 on OpenAlexaff
Andrej Spiridonov, S. Lovejoy, Lauras Balakauskas, Liudas Daumantas

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsMcGill University
Fundersnot available
KeywordsFossil RecordTectonicsScalingPaleontologyGeologyGeography

Abstract

fetched live from OpenAlex

The fossil record is the only direct source of information of the evolution, ecology, and biogeography of non-avian dinosaurs. The taphonomy is the science of the study of transition of biological information in to the stratigraphical record. The stratigraphical record is characterized by multiscale spatial and temporal structure. The largest scale structures are often called “megabiases”. Here we study the structure of megabiases of the dinosaurian fossil record from the Paleobiology Database in time as well as in space. We found a strong tendency of dinosaur occurrences to cluster at tectonic plate boundaries. Moreover, there are systemic temporal differences in the degree of this outward distribution of occurrences which are related to the sea level and the degree of tectonic fragmentation. Finally, we used spatial distributional patterns in simulating occurrences, and determined the effects of such inhomogeneities on the accuracy of determination of bioprovinces using newly developed R package ‘HespDiv’ for contiguous spatial cluster analysis.The study was supported by the grant by S-MIP-21-9 “The role of spatial structuring in major transitions in macroevolution”.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.030
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.218
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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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