Data from: Individual, ontogenetic, and phylogenetic variation in the dentition of hadrosaurids (Iguanodontia: Ornithischia)
Bibliographic record
Abstract
Phylogenetic analyses of Hadrosauroidea are generally well-resolved, but finer resolution within Hadrosauromorpha remains contentious. This lack of resolution is due in part to the inability of discrete traits to illustrate their natural variation, particularly relating to the dental tooth battery. Not only has the variation not been properly examined, but the character definitions fluctuate throughout the literature. Here, we evaluate individual, ontogenetic, and phylogenetic variation in four fundamental tooth characters at the subfamily level to better establish their use in future analyses: number of tooth rows, tooth aspect ratio, secondary enamel ridges, and marginal enamel denticles. Factor analysis of mixed data and linear discriminant analysis were used to evaluate how accurately these four characters together identified the phylogenetic groups. We then used these data to predict phylogenetic relationships for a select few historically problematic taxa. We found that although the number of tooth rows is phylogenetically informative, it is related to size and is only useful in separating hadrosaurids from non-hadrosaurid iguanodontians. Tooth aspect ratio was found to be highly variable, and phylogenetic groups cannot be separated reliably from one another. Secondary ridges are individually variable, and their presence or absence should be grouped into a single character instead of being separated. Lastly, the presence and shape of marginal denticles in hadrosaurids is similarly variable, though rounded mammillations are almost exclusive to Lambeosaurinae, with some variation in their presence and prevalence within the group. When used in combination, these characters can accurately identify dentary teeth below Hadrosauridae, providing new options for identifying poorly preserved specimens and isolated teeth from microsites. Taken together, these characters may still be informative, but the individual variation described here must be accounted for when constructing character states, and we recommend several modifications to their coding.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".