A landmarking protocol for geometric morphometric analysis of squamate endocasts
Bibliographic record
Abstract
Landmark-based geometric morphometrics is widely used to study the morphology of the endocast, or internal mold of the braincase, and the diversity associated with this structure across vertebrates. Landmarks, as the basic unit of such methods, are intended to be points of correspondence, selected depending on the question at hand, whose proper definition is essential to guarantee robustness and reproducibility of results. In this study, 20 landmarks are defined to provide a framework to analyze the morphological variability in squamate endocasts. Ten species representing a cross-section of the diversity of Squamata from both phylogenetic and ecological (i.e., habitat) perspectives were considered, to select landmarks replicable throughout the entire clade, regardless of the degree of neuroanatomical resolution of the endocast. To assess the precision, accuracy, and repeatability of these newly defined landmarks, both intraobserver and interobserver error were investigated. Estimates of measurement error show that most of the landmarks established here are highly replicable, and preliminary results suggest that they capture aspects of endocast shape related to both phylogenetic and ecologic signals. This study provides a basis for further examinations of squamate endocast disparity using landmark-based geometric morphometrics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.007 |
| 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) | 0.001 | 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 teacher head, 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".