Digit-only sauropod pes trackways from China – evidence of swimming or a preservational phenomenon?
Bibliographic record
Abstract
For more than 70 years unusual sauropod trackways have played a pivotal role in debates about the swimming ability of sauropods. Most claims that sauropods could swim have been based on manus-only or manus-dominated trackways. However none of these incomplete trackways has been entirely convincing, and most have proved to be taphonomic artifacts, either undertracks or the result of differential depth of penetration of manus and pes tracks, but otherwise showed the typical pattern of normal walking trackways. Here we report an assemblage of unusual sauropod tracks from the Lower Cretaceous Hekou Group of Gansu Province, northern China, characterized by the preservation of only the pes claw traces, that we interpret as having been left by walking, not buoyant or swimming, individuals. They are interpreted as the result of animals moving on a soft mud-silt substrate, projecting their claws deeply to register their traces on an underlying sand layer where they gained more grip during progression. Other sauropod walking trackways on the same surface with both pes and manus traces preserved, were probably left earlier on relatively firm substrates that predated the deposition of soft mud and silt . Presently, there is no convincing evidence of swimming sauropods from their trackways, which is not to say that sauropods did not swim at all.
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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 | 0.001 |
| 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 | 0.002 |
| 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".