High-resolution UAV maps of the Gobi Desert provide new insights into the Upper Cretaceous of Mongolia
Bibliographic record
Abstract
The Gobi Desert of southern Mongolia is home to an incredibly rich record of dinosaurs and other vertebrate fossils from the latest Cretaceous Period. Together, more than a dozen sites in several basins have produced one of the richest palaeofaunas known from this interval anywhere in the world. Most of this diversity has been recovered from the fluvial deposits of the Nemegt Formation. Despite historic and ongoing research in southern Mongolia, accurate maps and geological data for the main fossil sites are still lacking, limiting our ability to investigate how local palaeoecological dynamics influenced Nemegt taxa, their geographic distribution, and their evolutionary patterns. One of these sites, Guriliin Tsav, has produced more than a hundred significant fossil specimens to date, but still remains one of the lesser known Nemegt localities. In part this is because many expeditions have instead focused on the nearby Bügiin Tsav, one of the largest and richest localities for the Nemegt Formation. To address this gap, a project was initiated in 2018 to produce a high-resolution topographic map of Guriliin Tsav using Unmanned Aerial Vehicles (UAV), and consequently, to plot the geographic and stratigraphic distributions of palaeontological resources on this map. In so doing, we also collected stratigraphic and taphonomic data from the area, allowing for the first detailed palaeoecological interpretation of Guriliin Tsav and a comparison with other localities of southern Mongolia. Here we present the results of this project, and also discuss new topographic and stratigraphic data from Bügiin Tsav. This sheds new light into the temporal and geographic distribution of vertebrate taxa in the latest Cretaceous of Mongolia.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".