Statistical Approach for Classification of Dinosaur Eggs from the Heyuan Basin at the Northeast of Guangdong Province
Bibliographic record
Abstract
Abstract: The Zhutian and Dafeng formations (Upper Cretaceous) of the Heyuan Basin in northeastern Guangdong Province, China, have produced thousands of dinosaur eggs. Macromorphological features (egg diameter, egg shape, outer surface texture, and shell thickness) of 461 eggs were analyzed using non‐destructive techniques and subjected to statistical analyses in order to assess their diversity and taxonomic affinities. Three types (1, 2 and 3) of eggs were discerned based on shape and outer surface morphology. Type 1 eggs are spherical to ellipsoidal in shape and have a rough surface. Three subtypes (Type 1‐A‐1, 1‐A‐2, and 1‐B) are apparent from scatter plots and cluster analyses of egg diameters and shell thickness. Type 2 eggs are elongate with linear ornamentation on the surface, and are comparable to eggs that belong to the oofamily Elongatoolithidae. Type 3 eggs are elongate with a smooth surface, and are assigned to the oofamily Prismatoolithidae. Macromorphological features of the various egg types suggest that Type 1 could have been laid by ornithischian, sauropod or therizinosaur dinosaurs, Type 2 by oviraptorids, and Type 3 by troodontids. This study represents the first comprehensive statistical analysis of macrofeatures of dinosaur eggs, and reveals taxonomic diversity in the dinosaurs that were laying eggs in the Upper Cretaceous Heyuan area heretofore unrecognized in skeletal remains.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".