Computed tomography, anatomical description and three-dimensional reconstruction of the lower jaw of Eusthenopteron foordi Whiteaves, 1881 from the Upper Devonian of Canada
Bibliographic record
Abstract
The cranial anatomy of the iconic early tetrapod Eusthenopteron foordi is probably the best understood of all fossil fishes. In contrast, the anatomy of the lower jaw - crucial for both phylogenetics and biomechanical analyses - has been only superficially described. Computed tomography data of three Eusthenopteron skulls were segmented using visualization software to digitally separate bone from matrix and individual bones from each other. Here, we present a new description of the lower jaw of Eusthenopteron based on microcomputed tomography data, including the following: detailed description of sutural morphology and the mandibular symphysis; confirmed occurrence of pre- and intercoronoid fossae on the dorsal aspect of the lower jaw; and the arrangement of the submandibular bones. Furthermore, we identify a novel dermal ossification, the postsymphysial, present on the anteromedial aspect of the lower jaw in Eusthenopteron and describe its distribution in other stem tetrapod taxa. Sutural morphology is used to infer load regimes and, along with overall skull and lower jaw morphology, suggests that Eusthenopteron may have used biting along with suction feeding to capture and consume large prey. Finally, visualization software was used to repair and reconstruct the lower jaw, resulting in a three-dimensional digital reconstruction.
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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 | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".