Footprints of the earliest reptiles: Notalacerta missouriensis – Ichnotaxonomy, potential trackmakers, biostratigraphy, palaeobiogeography and palaeoecology
Bibliographic record
Abstract
The origin of reptiles in the tetrapod footprint record has always been a debated topic, despite the great potential of fossiliferous ichnosites to shed much light on reptile origins when compared to the much less extensive skeletal record. This is in part due to an unclear ichnotaxonomy of the earliest tracks attributed to reptiles that has resulted in unreliable trackmaker attributions. We comprehensively revise the earliest supposed reptile ichnotaxon, Notalacerta missouriensis , based on a neotype and a selection of well-preserved material from the type locality and other sites. A synapomorphy-based track-trackmaker attribution suggests eureptiles and, more specifically, ´protorothyridids´ such as Paleothyris as the most probable trackmakers. A revision of the entire Pennsylvanian-Cisuralian record of this ichnotaxon unveils an unexpected abundance and a wide palaeogeographical distribution. The earliest unequivocal occurrence of Notalacerta is in the middle Bashkirian (early Langsettian) at the UNESCO World Heritage Site, Joggins Fossil Cliffs (Joggins, Nova Scotia, Canada). This occurrence also coincides with the earliest occurrence of reptile body fossils ( Hylonomus lyelli ), which are found at the same site. Notalacerta is abundant and widely distributed during the Bashkirian, mostly in sediments deposited in tidal palaeoenvironments, and less common in the Moscovian and Kasimovian. During the Gzhelian and Asselian, Notalacerta occurrences are unknown, but it occurs again during the Sakmarian and is widespread but not abundant during the Artinskian, mostly in fully continental palaeoenvironments.
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 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".