Giant dinosaur eggs from the Tiantai basin, Zhejiang Province, China
Bibliographic record
Abstract
Giant dinosaur eggs occur within the mid-Cretaceous Liangtoutang Formation of the Tiantai basin in Zhejiang Province of southeastern China. The 43 cm × 14.5 cm eggs represent the first discovery of Macroelongatoolithus xixiaensis specimens from the region. The eggshell exhibits variation in surface ornamentation and eggshell thickness, with smoother and thicker eggshell characteristic of the poles. The Tiantai eggs differ from the stratigraphically younger type specimen of Macroelongatoolithus xixiaensis from Henan Province in their mammillary to continuous layer ratio. Three new features potentially useful for phylogenetic analysis and previously unreported in Macroelongatoolithus and other eggs in the oofamily Elongatoolithidae include prismatic columns, tabular structure within the prisms, and "splaying" of the crystals in the upper mammillae that extend into the overlying continuous layer. Microstructural features of the two nearly complete eggs suggest that the specimens are referable to a potentially large theropod dinosaur. Paleogeographic distribution of these large theropod eggs includes the Late Cretaceous Zoumagang Formation of Henan Province and the mid-Cretaceous Liangtoutang Formation of Zhejiang Province in central and southeastern China and possibly the Lower Cretaceous Cedar Mountain Formation and mid-Cretaceous Dakota Formation of Utah, USA.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".