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Record W4248025594 · doi:10.7287/peerj.preprints.434

A survey of dinosaur diversity by clade, age, place of discovery and year of description

2014· preprint· en· W4248025594 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsnot available
Fundersnot available
KeywordsCretaceousPaleontologyGeographyChinaBiologyZoologyArchaeology

Abstract

fetched live from OpenAlex

Dinosaur diversity is analyzed in terms of the number of valid genera within each major clade, Mesozoic age, place of discovery and year of description. Aves (Archaeopteryx + Neornithes) is excluded. Nomina nuda and nomina dubia are not counted. The results show 451 valid dinosaurian genera at the end of 2001, of which 282 are saurischian (112 sauropodomorphs and 170 theropods, including 93 coelurosaurs) and 169 ornithischian, including 11 pachycephalosaurs, 26 ceratopsians, 60 ornithopods, 12 stegosaurs, and 38 ankylosaurs. Thirty-eight genera arose in the Triassic, 124 in the Jurassic, and 289 in the Cretaceous, of which a disproportionately high number — 85 and 47 — are from the Campanian and Maastrichtian. The Kimmeridgian was the most productive age, with an average of 11.18 new genera per million years. The Kimmeridgian saw an unparalleled boom in sauropod diversity, with 20 new sauropod genera arising in its 3.4 million years, an average of one new sauropod every 170,000 years. Asia was the most productive continent with 149 genera, followed by North America (135), Europe (66), South America (52), Africa (39), Australasia (9), and finally Antarctica (1). Just three countries account for more than half of all dinosaur diversity, with 231 genera between them: the U.S.A (105), China (73), and Mongolia (53). The top six countries also include Argentina (44), England (30), and Canada (30), and together provide 335 dinosaur genera, nearly three quarters of the total. The rate of naming new dinosaurs has increased hugely in recent years, with more genera named in the last 19 years than in all the preceding 159 years. The results of these analyses must be interpreted with care, as diversity in ancient ecosystems is perceived through a series of preservational and human filters yielding observed diversity patterns that may be very different from the actual diversity.

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)0.002
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.006
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.218
Teacher spread0.185 · 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
Published2014
Admission routes1
Has abstractyes

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